Sri Lanka Economic Performance Assessment (2009)

Sri Lanka
Economic Performance
Assessment
September 2009
This publication was produced by Nathan Associates Inc. for review by the United States
Agency for International Development.

Sri Lanka
Economic Performance
Assessment
Disclaimer
The views expressed herein do not necessarily reflect those of the United States
Agency for International Development.

Nathan Associates Inc. has developed standard methodologies for producing analytical reports that provide
a clear and concise evaluation of economic growth performance in countries receiving USAID assistance,
including a special template for countries emerging from violent conflict. The reports are tailored to meet
the needs of USAID missions and regional bureaus for country-specific analysis. Each report contains
⎯ A synthesis of key data indicators from numerous sources, including the World Bank, the International
Monetary Fund, the Millennium Challenge Corporation, the United Nations, other international data
sets, and host-country documents and data sources;
⎯ International benchmarking to assess a country’s performance in comparison to similar countries,
groups of countries, and predicted values based on international data;
⎯ An analytic narrative that highlights areas in which a country’s performance is particularly strong or
weak, to assist in the identification of programming priorities; and
⎯ A Highlights Table and a Performance Scorecard summarizing the main report findings.
The authors of the present report are Rita Aggarwal, Michael Blackman, and Molly James of Nathan
Associates.
This work is sponsored by the Country Analytical Support (CAS) project of the Economic Growth office of
USAID’s Bureau of Economic Growth, Agriculture and Trade (EGAT) under contract no. PCE-I-00-00-
00013-00, task order 004 (2004–2006) and contract no. GEG-I-00-04-00002-00, task order 004 (2006–
2010).
Nathan Associates Inc. also assesses data issues in countries with large gaps in their data; conducts in-depth
sector reviews based on the diagnostic analysis in the country reports; and provides other analytical support
to the EGAT Bureau under the CAS project.
Economic performance assessments, economic recovery assessments, other CAS project reports, and data
used in making the assessments are available at www.countrycompass.com.
The COTR for the CAS project is Yoon Lee; C. Stuart Callison is the activity manager. USAID missions
and bureaus may seek assistance and funding for country analytical studies or in-depth follow-on studies by
contacting Mr. Callison at ccallison@usaid.gov. For further information about the CAS project, contact
Alexander Greenbaum, chief of party of the CAS Project, at agreenbaum@nathaninc.com

Contents
Highlights of Sri Lanka Performance iii
Sri Lanka: Strengths and Weaknesses—Selected Indicators iv
1. Introduction 1
Methodology 1
Data Quality and Format 2
2. Overview of the Economy 5
Conflict Background 5
Growth Performance 6
Poverty and Inequality 8
Economic Structure 10
Demography and Environment 11
Gender 13
3. Private Sector Enabling Environment 15
Fiscal and Monetary Policy 15
Business Environment 18
Financial Sector 21
External Sector 23
Economic Infrastructure 27
Science and Technology 28
4. Pro-Poor Growth Environment 31
Health 31
Education 33
Employment and Workforce 33
Agriculture 34

II
Appendix A. CAS Methodology
Appendix B. Data Supplement
Illustrations
Figures
Figure 2-1. Real GDP Growth, Percent Change 7
Figure 2-2. Gross Fixed Investment, Percent GDP 9
Figure 2-3. Output and Labor Force Structure 11
Figure 2-4. Population Living in Urban Areas 12
Figure 2-5. Labor Force Participation Rate 14
Figure 3-1. Inflation Rate 16
Figure 3-2. Rule of Law Index 20
Figure 3-3. Regulatory Quality Index 20
Figure 3-4. Domestic Credit to Private Sector, Percent GDP 22
Figure 3-5. Current Account Balance, percent GDP 24
Figure 3-6. Foreign Exchange Reserves, $US billions 26
Figure 3-7. Internet Users, per 100 people 28
Figure 4-1. Access to Improved Water 32
Figure 4-2. Cereal Yield, kilograms per hectare 35
Exhibit
Exhibit 2-1. Economic and Conflict Chronology in Sri Lanka, 2008–2009 6

HIGHLIGHTS OF SRI LANKA PERFORMANCE
Economic
growth
An average 6.4 percent growth rate for 2003-2008 masks a strong regional imbalance—nearly
half of GDP comes from the Western Province. Economic growth has slowed in 2009, but
growth potential is high since defeat of LTTE.
Poverty Although the national poverty rate has declined in recent years, stark regional disparities
persist and pose serious threats to stability.
Economic
structure
Demography and
environment
Growth of the services sector outpaced agriculture. In 2008, services produced 57.3 percent of
GDP and employed 42.1 percent of the workforce. Agriculture contributed 13.4 percent of
GDP and employed 31.3 percent of the workforce.
Moderate population growth and a relatively low age-dependency ratio favor economic and
human development. In the near term, the resettlement of an estimated 280,000 refugees poses
a formidable social and economic challenge for the government.
Gender Gender equity in health and education is excellent, but disparities in labor force participation
indicate that women have fewer opportunities for advancement.
Fiscal and
monetary policy
Business
Environment
The average annual inflation rate rose to 22.6 percent in June 2008 then fell to 14.4 percent in
December 2008 thanks to declining world oil prices and tightened monetary policy. At 7.7
percent of GDP in 2008, the budget deficit was one of the world’s highest. IMF targets call for
reducing the deficit to 5 percent of GDP by 2011.
Corruption, a confusing and somewhat opaque regulatory system, and diminished public
confidence in government commitment to the rule of law contribute to and reflect the
challenges facing businesses in Sri Lanka.
Financial sector State-owned banks still dominate. Private sector credit “crowded out” by government
borrowing and global recession reduced businesses’ own demand for credit. High interest rates
should come down with recent Central Bank moves to loosen monetary policy. Nonbank
financial services, such as leasing, are expanding.
External sector The current account deficit of 9.4 percent of GDP in 2008 was double that of 2007. Foreign
investors withdrew amid global crisis and exchange reserves dropped to dangerous lows. The
balance of payments is stabilizing in 2009.
Economic
infrastructure
Science and
technology
Poor transportation infrastructure deters investment and constrains businesses throughout the
country. Recent advances in telecommunications (phones and internet) are encouraging.
Intellectual capital is strong for a lower-middle income country. IPR protection has improved
in recent years but requires more attention.
Health Sri Lanka has a high life expectancy (72 years), low maternal mortality, and a low prevalence
of HIV, but high rates of child malnutrition and limited access to clean water remain concerns.
Education Education status indicators for Sri Lanka show nearly universal availability of primary
education. Yet low government spending on education (0.7 percent of GDP on primary
education in 2006) may be jeopardizing future achievement.
Employment and
workforce
Addressing ethnic-based disparities in employment will continue to be a challenge for the
government. The public sector workforce is large and the cost of firing redundant workers is
extremely high.
Agriculture Agriculture demonstrates low labor productivity, despite having high per hectare rice yields.
To improve sectoral performance, market based reforms need to be implemented to encourage
diversification into higher value-added production. Given that the Sri Lankan government
owns 80 percent of the land, tenure reforms and improved access to land are necessary to
increase the productivity of the agricultural sector.

IV
SRI LANKA: STRENGTHS AND WEAKNESSES—SELECTED
INDICATORS
Growth performance
Selected Indicators, by Topic Strengths Weaknesses
Real GDP growth X
Growth of labor productivity X
Investment productivity—incremental capital-output ratio (ICOR) X
Poverty and inequality
Population below minimum dietary energy consumption X
Demography and environment
Population growth rate X
Youth dependency rate X
Gender
Primary completion rates, male, female X
Labor force participation rates, female X
Fiscal and monetary policy
Government budget balance X
Government expense X
Business environment
Rule of law index X
Government effectiveness index X
Financial sector
Domestic credit to the private sector X
Money supply (M2), percent GDP X
External sector
Trade in goods and services, percent GDP X
Debt service ratio, percent exports X
Current account balance X
Foreign direct investment, percent GDP X
Trade in services, percent GDP X
Remittance receipts, percent GDP X
Economic infrastructure
Overall infrastructure quality X
Quality of infrastructure—rail X
Quality of infrastructure—electricity supply X
Internet users per 100 people X

Science and technology
Selected Indicators, by Topic Strengths Weaknesses
FDI technology transfer index X
Availability of scientists and engineers X
Health
HIV prevalence X
Life expectancy at birth X
Prevalence of child malnutrition X
Access to improved water source X
Education
Net primary enrollment rate X
Primary completion rate X
Expenditure on primary education X
Employment and workforce
Labor force participation rate X
Growth of labor force X
Rigidity of employment index X
Agriculture
Agriculture value-added per worker X
Cereal yield X
Note: The chart identifies selective indicators for which performance is particularly strong or weak relative to benchmark
standards, as explained in Appendix A. The data supplement presented in Appendix B provides full tabulation of the data and
international benchmarks examined for this report, along with technical notes on data sources and definitions.
V

1. Introduction
This report is one of a series of economic performance assessments prepared for the EGAT
Bureau to provide USAID missions and regional bureaus with a concise evaluation of key
indicators covering a broad range of issues relating to economic growth performance in
designated host countries. Each report draws on a variety of international data sources1 and uses
international benchmarking against reference group averages, comparator countries, and
statistical norms to identify major constraints, trends, and opportunities for strengthening growth
and reducing poverty. In this report, Sri Lanka’s economic performance is compared to that of
lower-middle-income (LMI) countries and LMI countries in Asia (median values) and to
performance in the Philippines and Thailand.
METHODOLOGY
The methodology used here is analogous to examining an automobile dashboard to see which
gauges are signaling problems. Sometimes a blinking light has obvious implications—such as the
need to fill the fuel tank. In other cases, it may be necessary to have a mechanic probe more
deeply to assess the source of the trouble and determine the best course of action. 2 Similarly, the
economic performance assessment is based on an examination of key economic and social
indicators, to see which ones are signaling problems. Some “blinking” indicators have clear
implications, while others may require further study to investigate the problems more fully and
identify appropriate courses for programmatic action.
The analysis is organized around two mutually supportive goals: transformational growth and
poverty reduction. 3 Broad-based growth is the most powerful instrument for poverty reduction.
At the same time, programs to reduce poverty and lessen inequality can help to underpin rapid
and sustainable growth. These interactions can create a virtuous cycle of economic transformation
and human development.
1 Sources include the World Bank, the International Monetary Fund, the Millennium Challenge
Corporation, the United Nations (including the Millennium Development Goals database), the World
Economic Forum, and host-country documents and data sources. This report reflects data available as of
July 2009.
2 Sometimes, too, the problem is faulty wiring to the indicator—analogous here to faulty data.
3 In USAID’s white paper U.S. Foreign Aid: Meeting the Challenges of the Twenty-first Century (January
2004), transformational growth is a central strategic objective, both for its innate importance as a
development goal and because growth is the most powerful engine for poverty reduction.

2 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
Transformational growth requires a high level of investment and rising productivity. This is
achieved by establishing a strong enabling environment for private sector development,
involving multiple elements: macroeconomic stability; a sound legal and regulatory system,
including secure contract and property rights; effective control of corruption; a sound and
efficient financial system; openness to trade and investment; sustainable debt management;
investment in education, health, and workforce skills; infrastructure development; and sustainable
use of natural resources.
In turn, the impact of growth on poverty depends on policies and programs that create
opportunities for and build capabilities among the poor. We call this the pro-poor growth
environment. Here, too, many elements are involved, including effective education and health
systems, policies facilitating job creation, agricultural development (in countries where the poor
depend on farming), dismantling barriers to micro and small enterprise development, and
progress toward gender equity.
The present evaluation must be interpreted with care. A concise analysis of selected indicators
cannot provide a definitive diagnosis of economic performance problems, nor simple answers to
questions about programmatic priorities. Instead, the aim of the analysis is to spot signs of serious
problems affecting economic growth, subject to limits of data availability and quality. The results
should provide insight about potential paths for USAID intervention, to complement on-theground
knowledge and further in-depth studies.
The remainder of the report presents the most important results of the diagnostic analysis, in four
sections: overview of the economy; private sector enabling environment; and pro-poor growth
environment. Table 1-1 summarizes the topical coverage. Appendix A briefly explains indictor
selection criteria and the benchmarking methodology, and lists all indicators examined for this
report. Appendix B provides a full tabulation of the data and international benchmarks examined
for this report, along with technical notes on the data sources and definitions.
Table 1-1
Topic Coverage
Overview of the Economy
• Growth performance
• Poverty and inequality
• Economic structure
• Demographic and environmental
conditions
• Gender
Private Sector Enabling
Environment Pro-Poor Growth Environment
• Fiscal and monetary policy
• Business environment
• Financial sector
• External sector
• Economic infrastructure
• Science and technology
• Health
• Education
• Employment and workforce
• Agriculture
DATA QUALITY AND FORMAT
The breadth and quality of data collected for Sri Lanka are comprehensive and current,
particularly the economic data. Some data for social conditions are dated, with reporting based on
2003/2004 figures. The World Bank gave Sri Lanka a score of 70 (out of 100) on its 2008
Statistical Capacity Indicator Index. This score is well above that expected for a country with Sri

I NTRODUCTION 3
Lanka’s characteristics and in line with the lower middle-income (LMI) Asia median score of
70.7, but well below scores for our country comparators: the Philippines (88) and Thailand (82).
Sri Lanka did not score well on statistical practice (50). The World Bank’s cites several problems,
such as the use of old base years for national accounts (1996) and price data (1952), a lack of
consolidated government accounts, and failure to adopt the IMF’s Special Data Dissemination
Standards (SDDS). Data on Sri Lanka’s northern and eastern provinces are very limited, though
this should improve dramatically as post-conflict reconstruction begins. It should also be noted
that this report uses poverty data from 2006/07 based on national surveys done by the Sri Lanka
Department of Census and Statistics. This data is not reported in the World Bank Social
Indicators dataset nor does the website for the Millennium Development Goals provide this in
their country datasheet for Sri Lanka, reporting instead data from 2002 household surveys.

2. Overview of the Economy
This section reviews basic information on Sri Lanka macroeconomic performance, poverty and
inequality, economic structure, demographic and environmental conditions, and indicators of
gender equity. Some of the indicators cited here are descriptive rather than analytical and are
included to provide context for the performance analysis.
CONFLICT BACKGROUND
Sri Lanka’s economic situation reflects the legacy of more than 25 years of armed conflict.
Drawing resources away from productive investment and leaving a large portion of the country
underdeveloped, the conflict arose after independence in 1948 when the Sinhalese, comprising
more than 80 percent of the population, implemented “Sinhala-only” laws that discriminated
against Tamils, who comprise about 14 percent of the population. Discriminatory policies in the
1960s and 1970s further antagonized and alienated the Tamil community.
In the early 1980s, the Liberation Tigers of Tamil Elam (LTTE) rose to prominence by
demanding a separate state for Tamils in the northern and eastern parts of Sri Lanka. Establishing
a stronghold in those regions for many years, the LTTE ran a separate government and financed
operations through a mix of extortion and contributions from the diaspora and other sympathetic
sources outside the country. Considered a terrorist organization by the United States, the LTTE
acted violently against the military forces of the Sinhalese government as well as moderate
Tamils who condemned the LTTE’s methods. The Government of Sri Lanka approved a military
intervention by India from 1987–1990, but this failed to suppress the LTTE, and was followed in
May 1991 by the assassination of Rajiv Ghandi, a female LTTE suicide bomber. Periodic cease
fires brokered by other countries and donors always relapsed into fighting. In 2006, the
government of Mahinda Rajapaksa stepped up its efforts to defeat the LTTE and proclaimed
victory in May 2009. Exhibit 2-1 traces events of 2008 leading up to this proclamation.
The final months of the war displaced more than 280,000 people, most of them still in camps as
of August 2009. The government maintains that refugees must be screened for hard core LTTE
cadres before release and resettlement and that resettlement lands must be cleared of mines.
Resettling and rebuilding the north and east will be a formidable task, as will accommodating the
aspirations of the Tamil minority for economic opportunities and a meaningful voice in their own
governance.

6 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
Exhibit 2-1
Economic and Conflict Chronology in Sri Lanka, 2008–2009
2008
January. Government pulls out of 2002 ceasefire
agreement.
June. Inflation rate peaks at 28.2 percent.
July. Sri Lankan military says it has captured the Tamil
Tigers naval base of Vidattaltivu in the north.
November. Foreign exchange reserves stood at $1.7
billion, the equivalent to 1.5 months of imports.
December. Sri Lankan troops and Tamil rebels claim to
have inflicted heavy casualties on each other in the north.
2009
January. Government troops capture the northern town
of Kilinochchi, held for ten years by the Tamil Tigers as
their administrative headquarters. President Rajapakse
claims unparalleled victory and urges the rebels to
surrender.
February. International concern for thousands of
civilians trapped in the battle zone prompts calls for a
cease-fire. Claiming it is on the verge of destroying the
Tamil Tigers the government rejects a cease fire but
SOURCE: BBC News and additional economic news sources.
offers amnesty to rebels if they surrender. Tamil Tiger
planes conduct suicide raids against Colombo.
February. Inflation rate drops to 7.6 percent, reaching
single digits for first time since July 2006.
March. Former rebel leader Karuna is sworn in as
minister of national integration and reconciliation. United
Nations High Commissioner for Human Rights Navi
Pillay accuses both sides of war crimes.
The government rejects conditions attached to an IMF
emergency loan worth $1.9 billion, denies U.S. pressure
causing delay to agreement.
May. Government declares Tigers defeated after army
forces overrun last patch of rebel territory. Military says
rebel leader Velupillai Prabhakaran was killed in the
fighting. Tamil Tiger statement says the group will lay
down its arms.
July. IMF approves $2.6 billion loan to stabilize balance
of payments crisis.
August. Foreign exchange reserves built up to $2.2
billion. First post-war local elections in north. Governing
coalition wins in Jaffna but in Vavuniya voters back
candidates who supported Tamil Tigers.
GROWTH PERFORMANCE
From 2003 to 2008 Sri Lanka enjoyed strong economic growth, with GDP growth averaging 6.4
percent. In 2008, despite the fourth quarter economic crisis, Sri Lanka managed an impressive 6
percent increase in GDP. In comparison the Philippines grew 4.6 percent and Thailand merely 2.6
percent in 2008. Sri Lanka performed above its expected value of 4.1 percent and measured up to
its LMI-Asia (6.4 percent) and LMI (5.8 percent) peers (Figure 2-1).
Per capita GDP has nearly doubled in the past few years, going from $1,063 in 2004 to $1,972 in
2008. However, this average increase in the standard of living for Sri Lankans masks huge
regional inequities; the west contributed a whopping 48.4 percent of GDP in 2007 while the
conflict-ridden north contributed a mere 2.9 percent (see Poverty and Inequality). 4
4 Central Bank of Sri Lanka, National Output and Expenditure, Gross Domestic Product by Province at
Current Factor Cost Prices (2003-2007), Table 4.

O VERVIEW OF THE E CONOMY 7
Figure 2-1
Real GDP Growth, Percent Change
Despite respectable growth, Sri Lanka faces significant macroeconomic challenges.
10.0
8.0
6.0
4.0
2.0
0.0
Time Series Comparisons to other countries, most recent year
2004 2005 2006 2007 2008
Year Value
2004 5.4
2005 6.2
2006 7.7
2007 6.8
2008 6.0
Summary for 2004-2008
Five year average 6.4
Trend growth rate 2.6
Percent Change
7
6
5
4
3
2
1
0
4.1
Expected value and margin of error
6.0 6.4 5.8 4.6 2.6
S ri L a nka LMI-As ia LMI P hilippines Thailand
Sri Lanka Global
Standing
Highest-five average
0.3
14.3
LKA
Lowest-five average
SOURCE: IMF World Economic Outlook CAS code: 11P3
Despite Sri Lanka’s high growth rates, the country has struggled with significant macroeconomic
imbalances due to the financing of expansive budget deficits. This left the country particularly
vulnerable to the external shocks emanating from the global crisis that started in 2008. The
country’s current account deficit on its balance of payments soared to 9.4 percent of GDP,
inflation rates doubled those of just two years earlier, and an effort to stabilize a depreciating
currency left gross official reserves at the end of the year sufficient for only for 1.5 months of
imports.
In early 2009 many observers believed that Sri Lanka was teetering on the brink of
macroeconomic disaster. 5 But the decisive victory over the LTTE in May 2009, improvements in
monetary and exchange rate policy, and a rebounding trade account pulled Sri Lanka from the
edge. The country has since negotiated an IMF $2.6 billion stand-by agreement and foreign
investors are returning, stabilizing the balance of payments situation. Other donors are also now
increasing aid. The IMF is forecasting a GDP growth rate of 3 percent for 2009, and some Sri
Lankan authorities project even higher growth. 6
5 Domestic oil prices remained relatively stable because of price controls imposed before 2006, but
gradual lifting of controls in 2006 and 2007 resulted in domestic inflation when international oil prices
increased. See Nombulelo Duma, Pass-Through of External Shocks to Inflation in Sri Lanka, IMF Working
Paper 08/78.
6 The central bank was forecasting 6 percent GDP growth for 2009 in January 2009. Sri Lankan Daily
News and Reports, January 2009.

8 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
The “peace dividend” and Sri Lanka’s proximity to the already reviving Indian economy mean
that growth could indeed accelerate, and be distributed more equitably, but several
macroeconomic indicators, particularly the large fiscal deficit, poses a serious challenge that
needs the government’s immediate attention. These points
are elaborated on in the discussion of the External Sector in
IMF Stand-By Arrangement
Section 3.
The incremental capital-output ratio (ICOR) is the amount of
investment needed per unit of additional output; a low ratio
signals efficiency. Sri Lanka’s average ICOR declined from
5.9 during the 2001–2005 period to 3.7 during the 2006–
2008 period, indicating tremendous gains in capital
efficiency. In fact, countries where capital is used most
productively typically have an ICOR of 4 or less. Here, Sri
Lanka compares favorably with ICORs for LMI-Asia (4.9),
LMI countries (4.7), and Thailand (4.8).
Sri Lanka’s approximately $2.6 billion
20-month stand-by arrangement with
the IMF aims to help it rebuild its
international reserves, reduce the fiscal
deficit to a sustainable 5 percent of
GDP by 2011, and strengthen the
financial sector. IMF funds will
increase central bank reserves rather
than financing budget expenditures. An
initial disbursement of about $322
million was made upon approval.
In addition to its increased capital efficiency, Sri Lanka’s
labor efficiency increased. In 2007 Sri Lanka’s labor productivity increased 4.5 percent. In
contrast, the Philippines grew 3.2 percent and Thailand increased 4.1 percent.
In 2008, gross fixed investment in Sri Lanka was 25.3 percent of GDP—matching the regression
benchmark value (25.7 percent), better than the LMI-Asia median (25 percent) and the LMI
median (24.3 percent), much better than the Philippines’ average (14.8 percent) but outpaced by
Thailand’s average of 26.8 percent (2007) (Figure 2-2). Sri Lanka’s investment rate, however, has
not grown significantly in recent years and much higher rates—on the order of 30 percent or
more—will be needed to sustain the high growth rates in other industrializing Asian nations.
These issues will all be discussed in greater detail in other sections of this report, but lower levels
of investment are largely attributable to the government’s habit of spending more than it collects
and to military spending, which absorbs resources that could be productively invested in
infrastructure and other efforts to improve the business climate. The conflict in the north and east
also impeded growth in tourism, fisheries and agriculture—industries that could have thrived in
the absence of conflict.
POVERTY AND INEQUALITY
Widespread poverty and inequality are related to a lack of security, education, health, income,
and employment opportunities. Moreover, high levels of poverty and extreme income inequality
can be prime motivators for political unrest, ethnic grievances, and outright civil strife. 7
In Sri Lanka, widespread poverty and inequality pose continuing threats to political and economic
stability and complicate the post-war recovery. Despite a decline in the poverty rate from 22.7
7 Paul Collier, The Bottom Billion: Why the Poorest Countries are Failing and What Can be Done About
It, London: Oxford University Press, 2007, 19.

O VERVIEW OF THE E CONOMY 9
percent in 2002 to 15.2 percent in 2006/07, 8 regional disparities are significant. The poverty rate
of Western province (8.2 percent) contrasts sharply with the country’s poorest provinces in south
central Sri Lanka Uva (27 percent) and Sabaragamuwa (24.2 percent). Moreover, the gap between
households—urban, rural and estate (covering tea, rubber and coconut sectors)—has widened
since 1990/91. The urban rate has declined by 59 percent and the rural rate by 47 percent, while
the rate among estate households has increased 56 percent. 9 Data are not available for the
Northern Province and the Trincomalee district, regions most affected by the conflict.
Figure 2-2
Gross Fixed Investment, Percent GDP
Although gross fixed investment has grown, it is still insufficient to sustain rapid growth.
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Time Series Comparisons to other countries, most recent year
2004 2005 2006 2007 2008
Year Value
2004 22.6
2005 23.4
2006 24.9
2007 24.7
2008 25.3
Summary for 2004-2008
Five year average 24.2
Trend growth rate 2.8
Percent GDP
30
25
20
15
10
5
0
25.3 25.0 24.3 14.8 26.8
S ri L a nka LMI-As ia LMI P hilippines Thailand
Sri Lanka Global
Standing
Highest-five average
9.5
51.4
LKA
Lowest-five average
SOURCE: Sri Lanka Central Bank and World Development Indicators 2009 CAS code: 11S3
Malnutrition is a concern. According to the Household Income and Expenditure Survey
(2006/07), half of the Sri Lankan population (50.7 percent) lack adequate dietary energy
consumption. 10 Sri Lanka’s malnutrition rate has remained static since 1990 (50.9 percent).
About one-third of the population is employed in agriculture (see Economic Structure). This
makes the population susceptible to external shocks such as drought and flooding.
8 Department of Statistics. Poverty in Sri Lanka (Based on Household Income and Expenditure Survey
2006/07), 2. Data for this survey was collected in monthly rounds from July 2006 to June 2007. The survey
excludes the districts in the Northern Province and Trincomalee district.
9 Department of Statistics. Poverty in Sri Lanka (Based on Household Income and Expenditure Survey
2006/07), 6.
10 The FAO defines undernourishment as the condition of people whose dietary energy consumption is
continuously below a minimum dietary energy requirement for maintaining a healthy life and carrying out
light physical activity.

10 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
Sri Lanka’s performance on the UNDP’s Human Poverty Index (HPI) indicates some
improvement in conditions for the poor. This index provides a broad gauge of poverty that takes
into account deprivation in health and education as well as income poverty. On a scale of 0 (zero
deprivation incidence) to 100 (high deprivation incidence), Sri Lanka’s score decreased
marginally from 17.7 in 2002 to 16.9 in 2006. This score, however, is worse than scores for
Thailand (9.0) and the Philippines (12.5) and much worse than the score expected for a country
with Sri Lanka’s characteristics (7.3).
National statistics, although dated, show that the poorest 20 percent of the population held only a
3.6 percent share of income in 2003/04, down from 4.1 percent in 1996/97. 11 This is below the
Philippines 5.6 percent (2006) and the LMI median and Thailand, both 6.1 percent (2004). Now
that the conflict in the north and east has ended, more attention can be paid to improving the
livelihoods of the poor in those areas
ECONOMIC STRUCTURE
According to Sri Lanka’s Central Bank, agriculture contributed 13.4 percent to GDP in 2008, a
slight increase from an average contribution of 11.6 percent between 2005 and 2007.
Agriculture’s share of GDP in Thailand was only 11.4 percent and in the Philippines 14.1 percent.
The LMI-Asia median share was 18.4 percent. According to the Asian Development Bank, Sri
Lanka’s agricultural sector grew 7.5 percent in 2008. This increase is largely attributable to
reclamation of abandoned rice paddies driven by the government’s commitment to increasing
domestic production. Future agricultural growth would be best facilitated by better land titling
and conciliatory government policy in former conflict areas.
Industry’s share of GDP has remained stagnant, coming in at 29.4 percent in 2008, slightly above
the expected value of 28.2 percent. These values were less than those for LMI-Asia (39.3
percent), the Philippines (31.7 percent), and Thailand (43.9 percent) (2007). The industrial base
remains concentrated in the garments, processed food, and chemical and plastic products
industries. The infrastructure projects now being planned for the north should spur growth in
construction and manufacturing.
Outpacing growth in agriculture and industry, growth in Sri Lanka’s services sector dominates the
economy, with telecommunication services prominent. In 2008, 57.3 percent of GDP was from
this sector. This is close to the expected value (58.1 percent) and exceeding shares in LMI-Asia
(45.1 percent), the Philippines (54.2 percent), and Thailand (44.7 percent) (2007).
Agriculture’s share of employment has been declining and was 31.3 percent in 2008, far below
shares in the Philippines (37 percent) and Thailand (42.6 percent) (2005). Meanwhile
employment in industry (26.6 percent) and services (42.1 percent) has increased slightly (see
Figure 2-3). Although industrial exports (e.g., garments) and services (e.g. hotels and restaurants)
have been hurt by the global economic downturn, they are both relatively more productive than
agriculture. Workers are continuing the decade-long shift from low-productivity agriculture to
higher value-added activities.
11 Central Bank, Special Statistical Appendix, Table 9; excluding Northern and Eastern Provinces.

O VERVIEW OF THE E CONOMY 11
Figure 2-3
Output and Labor Force Structure
Service sector productivity exceeds agricultural productivity
Percent of GDP
P e rce nt Tota l
100
90
80
70
60
50
40
30
20
10
0
100
90
80
70
60
50
40
30
20
10
0
Comparisons to other countries, most recent year
57.3
29.4
Output Structure
Agriculture, Value Added Industry, Value Added Services, etc., Value Added
54.2
31.7
44.7
43.9
13.4 14.1 11.4
S ri La nka P hilippines Thailand
42.1
31.3
Employment Structure
Agriculture Industry S ervices
48.1
26.6 14.9
37.0
37.1
20.2
42.6
S ri L a nka P hilippines Thailand
Source: Sri Lanka Central Bank and World Development Indicators 2009 CAS Code: 13P2a-c, 13P1ac
DEMOGRAPHY AND ENVIRONMENT
Sri Lanka’s population of 20.2 million is growing by an estimated 1.0 percent per year. 12 This
moderate pace translates into a relatively low and declining youth dependency ratio. In the five
years to 2007, this ratio fell from 36.8 dependents per 100 working age adults to 33.4
dependents. 13 This is well below the LMI-Asia median of 52.1 and the Philippines’ 58.5, and
nearing Thailand’s 30. Moderate population growth and a low age-dependency ratio reduce the
12 Sri Lanka Central Bank, Statistical Appendix, April 2009, Table 49.
13 2008 data from the Department of Census and Statistics indicate a slightly higher youth dependency
rate of 36.3 percent. The WDI figure is used here for benchmarking purposes.

12 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
household consumption burden for income earners and ease demand for public services, thereby
favoring economic and human development. They also reduce the number of those entering the
labor market. Coupled with appropriate labor market policies these trends favor faster growth and
more youth employment. Also favorable is Sri Lanka’s adult literacy rate of 91 percent (2006).
This is in line with the expected value for a country with Sri Lanka’s characteristics but below the
LMI-Asia median and literacy rates in the Philippines (93.4 percent) and Thailand (94.1 percent).
Sri Lanka has a decidedly rural population; more than 85 percent live in rural areas (Figure 2-4).
Rural density is also a high 1,823 persons per square kilometer of land, much higher than in the
Philippines (553) and Thailand (300). 14 High rural density increases pressure on land and natural
resources. In addition, competing claims on land by returning refugees and the current land
cultivators can be a source of violent conflict. This could be an immediate problem in northern
and eastern Sri Lanka where an estimated 280,000 (mostly Tamil) displaced persons are being
housed in refugee camps. 15 Refugees must be resettled rapidly to restart economic growth in the
north and ensure that the displaced are involved in rebuilding. The environmental and health
conditions in refugee camps, such as Manik Farms, are below UN standards and the health and
safety of refugees is threatened by insufficient supplies of water, overcrowding, and poor
sanitation.
Figure 2-4
Population Living in Urban Areas
Only 15 percent of Sri Lankans live in urban areas.
Percent
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Comparisons to other countries, most recent year
15.1 32.6 50.0 64.2 33.0
S ri L a nka LMI-As ia LMI P hilippines Thailand
Sri Lanka Global
Standing
Highest-five average
12.4
100
LKA
Lowest-five average
SOURCE: World Development Indicators 2009 CAS code: 14P5
14 World Development Indicators, 2008.
15 Can Peace Succeed? www.asia-monitor.com, accessed 13 August 2009.

O VERVIEW OF THE E CONOMY 13
National environmental indicators for Sri Lanka, however, are positive in comparison to other
countries in its income group. Sri Lanka scores well on the Environmental Performance Index
(EPI), a broad gauge of environmental sustainability compiled by Yale and Columbia. Sri
Lanka’s score is 79.5 (on an ascending scale of 0 to 100), which is higher than the LMI-Asia
median of 60.4 and LMI median of 64.8 and slightly above the Philippines’ 77.9 and Thailand’s
79.2.
Donor assistance will be critical to ensure the rapid resettlement of refugees displaced by the war.
Donors can also support policies to diminish water pollution and increase access to potable
ground water (see discussion under Health).
GENDER
Gender equity enables faster economic growth by ensuring that the productive capacities of all
citizens can be developed and used to their full extent. Sri Lanka performs well on most basic
indicators of gender equity, with the exception of labor force participation.
A fundamental gauge of gender equity in health conditions and living standards is life expectancy
at birth. In Sri Lanka, average life expectancy in 2006 was 75.8 years for women, compared to
68.2 years for men. This 7.6 year difference in favor of women conforms to the international
norm. In countries with an advanced level of human development, women live about five more
years than men. In Thailand, the life expectancy for women is 74.7 years, and the gender gap is
even wider at 9.1 years.
There is also a differential in favor of females in the gross enrollment ratio at all levels of
schooling (primary through tertiary). In 2006, this rate was 69.9 percent for females and 67.5 for
males. This gender differential of 2.4 percentage points is better than the Philippines’ 3.8
percentage point differential and on par with Thailand.
As in many developing countries, a significant gender disparity exists in labor force participation.
In 2007, 75.2 percent of working-age males and just 42.8 percent of working-age females were in
the labor force. This 32.4 percentage point differential is higher than all benchmarks (Figure 2-
5). 16 The unemployment rate among females in Sri Lanka (7.9 percent) was also higher than
males (4.2 percent) in the first quarter of 2009—and this trend is even more pronounced in the
central and northern regions. 17 This level of gender inequality in the labor markets seriously
undermines the country’s productive potential.
As women in Sri Lanka progress in educational achievement, policymakers would do well to
focus on creating equitable opportunities for women in the workplace so that all Sri Lankans can
fulfill their productive potential and contribute to national development.
16 Sri Lanka Department of Census statistics show slightly lower labor force participation rates for 2007
(68.2 percent males and 33.7 percent females) and 2008 (67.6 percent males and 35.0 percent females). The
WDI statistics are used here for benchmarking purposes.
17 Department of Census and Statistics. Quarterly Report of the Sri Lanka Labour Force, Q1 2009.

14 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
Figure 2-5
Labor Force Participation Rate
Gender inequality in the labor force reduces Sri Lanka’s
productive capacity.
Percent
90
80
70
60
50
40
30
20
10
0
Comparisons to other countries, most recent year
Labor Force Participation Rate, Male Labor Force Participation Rate,Female
75.2 42.8 80.7 52.7 77.8 49.4 80.4 49.8 80.5 65.7
S ri L a nka LMI-As ia LMI P hilippines Thailand
SOURCE: World Development Indicators 2009 CAS code: 15P4

3. Private Sector Enabling
Environment
This section reviews key indicators of the enabling environment for encouraging rapid and
efficient growth of the private sector. Sound fiscal and monetary policies are essential for
macroeconomic stability, which is a necessary though not sufficient condition for sustained
growth. A dynamic market economy also depends on basic institutional foundations, including
secure property rights, an effective system for enforcing contracts, and an efficient regulatory
environment that does not impose undue barriers on business activity. Financial institutions play a
major role in mobilizing and allocating saving, facilitating transactions, and creating instruments
for risk management. Access to the global economy is another pillar of a good enabling
environment because the external sector is a central source of potential markets, modern inputs,
technology, and finance, as well as competitive pressure for improving efficiency and
productivity. Equally important is development of the physical infrastructure to support
production and trade. Finally, developing countries need to adapt and apply science and
technology to attract efficient investment, improve competitiveness, and stimulate productivity.
FISCAL AND MONETARY POLICY
The sustainability of Sri Lanka’s 5 percent to 6 percent growth rate is in question given the
country’s persistently high budget and trade deficits, as well as rising inflation. Significant
macroeconomic imbalances came to a head in 2008 as inflation rose to more than 20 percent then
peaked in June at 28.2 percent. Import prices for oil and food rose as a result of the 2008 global
economic crisis, but domestic fiscal and monetary policies contributed heavily to inflation;
neighboring countries experiencing similar supply side shocks had inflation rates half that of Sri
Lanka’s. The Philippines and Thailand had an inflation rate of 9.3 percent and 5.5 percent
respectively, while the LMI-Asia median was 7 percent and the LMI region experienced an
inflation rate of 8.3 percent (Figure 3-1). 18
18 The IMF and others have documented that external supply shocks were not the primary reason for Sri
Lanka’s high inflation rates.

16 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
Figure 3-1
Inflation Rate
T he inflation rate has fallen significantly after reaching double digit highs in 2008.
25.0
20.0
15.0
10.0
5.0
0.0
Time Series Comparisons to other countries, most recent year
2005 2006 2007 2008 2009
Year Value
2005 11.0
2006 10.0
2007 15.8
2008 22.6
2009 4.6
Summary for 2005-2009
Five year average 12.8
Trend growth rate -9.3
Annual Percent Change
10
9
8
7
6
5
4
3
2
1
0
Expected value and margin of error
5.4
4.6 7.0 8.3 9.3 5.5
S ri L a nka LMI-As ia LMI P hilippines Thailand
Sri Lanka Global
Standing
*excluding Zimbabwe
Highest-five average
1.4
26.2
LKA
Lowest-five average
SOURCE: IMF Press release and World Economic Outlook database CAS code: 21P4
An obvious culprit behind Sri Lanka’s high inflation is the budget deficit, which has hovered
around 7 percent of GDP (including grants) in recent years then shot up to 7.7 percent in 2008 to
become one of the highest in the world. The severity of the imbalance is evident when one notes
that the budget deficit in the Philippines was 0.9 percent of GDP while Thailand maintained a
budget surplus of 0.8 percent in 2008.
The budget deficit is the result of low government revenues and high expenditures. Between 2006
and 2008 revenues averaged around 15 percent of GDP, roughly half of the amount predicted by
the regression benchmark (32 percent of GDP), while expenditures were maintained at around 23
percent of GDP. In 2008, revenues declined significantly as the government reduced import
tariffs on food and cut the value-added tax on gasoline in order to dampen the effects of the
economic downturn. 19 In the final months of 2008 sharp drops in imports and exports reduced
export and import taxes, thereby reducing overall government revenues.
The widening of the deficit was in large part due to the government’s renewed commitment to
fighting the LTTE in 2006. From 2006 to 2008, defense spending jumped 56 percent 20 and in
19 However, in late 2008, it resorted to ad hoc cesses to raise additional revenue, and cess revenue now
accounts for 4.3% of the total tax take, up from 1.4% in 2006. This development has made the tax system
increasingly complex and the 2009 budget called for a presidential task force to plan a rationalization.
Narhari Rao and Nimali Hasitha Witckremasinghe, “Sri Lanka” Asian Development Bank, 2009 Outlook.
20 Data from Sri Lanka Central Bank, Statistical Appendix, 2008, data for 2008 are provisional. Table
100.

P RIVATE S ECTOR ENABLING E NVIRONMENT 17
2008 military spending comprised 23 percent of all expenditures and 5 percent of GDP. Sri Lanka
has a large army for a country its size with180,000 regular troops. It has also invested heavily in
weapons systems. 21 The military defeated the LTTE in May 2009, but it is still in charge of
supervising the 280,000 Tamils in refugee camps and defense expenditures are unlikely to be
reduced in 2009 or 2010.
Other expenditures include various subsidies, particularly on fertilizer for the agriculture sector,
which puts pressure on the budget as international prices for this input increase. Public sector
salaries and wages are high, as is the cost of debt repayment. The costs of deficit financing are
huge, with interest payments accounting for 28 percent of expenditures in 2008. 22
With the recent end to the military conflict, the government should be able to focus on productive
investments that improve the investment climate. Already there is great interest in infrastructure
projects to reduce transportation costs. Sri Lanka may also benefit from grant funding that donors
were unwilling to provide during the conflict.
The government’s expansionary fiscal policy of the years before the global crisis cannot be
sustained in the post-conflict period. The IMF loan has a target fiscal deficit of 5 percent of GDP
by 2011 and increased domestic resource mobilization has to be a top priority. The government’s
2009 budget proposes to set up a presidential task force to rationalize national tax policy; and it is
hoped that tax collection will be improved by broadening the tax base, reducing exemptions, and
increasing enforcement. Revenue collected from personal income, profits, and capital gains as a
percent of total revenue is significantly lower than comparator countries at 19.3 percent, while
high import duties and export taxes generated 15 percent of revenue. Trade taxes as a percent of
all taxes in Sri Lanka are much higher than in Thailand (5.5 percent) but lower than in the
Philippines (average 20 percent).
Monetary Policy
To finance the deficit the government has been borrowing from the Central Bank of Sri Lanka
(CBSL) and commercial banks, and more recently from foreign commercial sources (see
discussion of External Sector below). The CBSL has been a “buyer of last resort” for the
government, purchasing unsold Treasury bills below market rates to finance government
borrowing. The resulting increases in the money supply have contributed significantly to the high
inflation rates of the past few years. The sharp spike in inflation in June 2008, however, was
caused primarily by the rise in world oil prices. Plummeting oil prices in the last quarter of 2008,
along with tightened monetary policy, led to a decline in domestic prices. 23 The 2009 inflation
rate is estimated to be 4.6 percent, falling from an annual average of 22.6 percent in 2008.
21 “Sri Lanka faces demons beyond the war; Army burden stunts economy”, theage.com.au, author: Matt
Wade, January 24, 2009. Source: http://www.theage.com.au/world/sri-lanka-faces-demons-beyond-thewar-20090123-7onw.html?page=-1
22 Sri Lanka Central Bank Statistical Appendix. Table 100.
23 The CBSL lowered reserve money growth targets three times in 2008, from 14.7 percent to 9.7
percent. Asian Development Bank, Sri Lanka 2009 Outlook.

18 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
As the global recession set in at the beginning of 2009, the CBSL once again began relaxing
monetary policy by lowering interest rates. In January 2009 it lowered the penal rate, which it
uses when lending to commercial banks who need extra funds to balance their level of cash
reserves, by 200 basis points to 17 percent, 24 and in June reduced the repurchase rate to 8.5
percent and reverse repurchase rate to 11 percent, after having frozen both for the previous 22
months. The shift in monetary policy to a growth orientation seems justified given the depth of
the global recession, the declining trend in global and domestic inflation, and the need to replace
falling income from exports with domestic economic activity.
Commercial banks had raised nominal interest rates in 2008 in response to high inflation and
although prices have come down, real interest rates have been high for much of 2009 (the interest
rate on Treasury Bills has been 18 percent), making it even harder for the private sector, already
suffering from declining sales, to get new credit. 25
Whether the CBSL will reduce rates even further remains to be seen, as lower rates may have
negative implications for the exchange rate and cause further depreciation of the currency. A
lower value of the rupee would make it difficult for the government to pay back debt
denominated in dollars. Years of borrowing to be able to spend more than what was collected
have left the government with little room to maneuver as it tries to restore macroeconomic
stability.
BUSINESS ENVIRONMENT
Institutional barriers to doing business, including corruption in government, are critical
determinants of private sector development and prospects for sustainable growth. The legal,
regulatory, and institutional underpinnings of the economy are crucial determinants of both
private sector and broader economic growth. Institutional inefficiencies or barriers, including
government corruption, stymie economic development.
In the World Bank’s Doing Business 2009 report (which uses 2008 data), Sri Lanka is ranked 102
overall, making it the leading reformer for business regulation in South Asia. This composite
index features several performance measures, including number of procedures for starting a
business, registering property, and enforcing contracts. While on these and other measures Sri
Lanka falls within international norms and has relatively good standing in South Asia, it would do
well to improve its business environment.
For example, it takes 1,318 days to enforce a contract in Sri Lanka, which compares poorly with
the expected value (652 days) and the LMI-Asia median (591 days), and the time it takes in
Thailand (479 days) and the Philippines (842 days). And even though Sri Lanka is a booming
transshipment hub for India, it ranks 66 out of 81 countries on trading across borders, which
24 Lanka Business Online, Rate Cut (January 12, 2009) Source:
http://www.lankabusinessonline.com/fullstory.php?nid=1633856703 Accessed August 31, 2009
25 Global Insight, Monetary Easing Cycle Extended in Sri Lanka. June 16, 2009. The press release by the
SLCB in January 2009 indicates that it feels less risk of inflation and expects banks to lower their interest
rates for lending.

P RIVATE S ECTOR ENABLING E NVIRONMENT 19
gauges time and costs associated with importing and exporting. Meanwhile, the Philippines is
ranked at 58 and Thailand at 10. Sri Lanka’s rank is consistent with observations that trade
protectionism—additional import taxes, customs delays, and extra charges—is on the rise. 26
In other areas measured by the Doing Business Indicators, including those directly relevant to
foreign direct investment, Sri Lanka’s performance is mixed in relation to comparators. On
average, it takes 83 days to register property in Sri Lanka compared to 50 days in LMI-Asia, only
33 days in the Philippines, and a mere 2 days in Thailand. On investment protection measures Sri
Lanka (70) performs better than the Philippines (126), but not nearly as well as Thailand (11).
The protecting investors index measures the strength of minority shareholder protections against
directors’ misuse of corporate assets for personal gain along three dimensions: transparency and
extent of disclosure, liability for director self-dealing, and shareholders’ ability to sue officers and
directors for misconduct. On the employing workers index, which measures the costs of hiring
and firing workers and the rigidity of working hours, Sri Lanka (110) performs better than the
Philippines (126), but far worse than Thailand (56).
Corruption and governance continue to be problems. Over the past three years Sri Lanka’s score
on Transparency International’s Corruption Perceptions Index has averaged 3.16. Scores below 5
indicate a serious corruption problem in the public sector, while a score of 3 verges on rampant
corruption. In 2008, Sri Lanka (3.2) falls in between Thailand (3.5) and the Philippines (2.3).
Sri Lanka’s scores on the World Bank’s Rule of Law and Regulatory Quality indices also point to
serious governance problems. Both indices score performance on a scale of -2.5 to +2.5, with a
mean of 0. Sri Lanka‘s rule of law score deteriorated from 0.04 in 2007 to -0.01 in 2008. This
contrasts favorably, however, with the Philippines (-0.49 in 2008) and LMI-Asia (-0.43) and
Thailand (-0.3) (See Figure 3-2). According to the International Bar Association, executive
discretion over judicial appointments makes the judiciary vulnerable to executive interference and
jeopardizes its independence. The failure of the Government of Sri Lanka to re-establish the
Constitutional Council has eroded public confidence in its commitment to independent
institutions and the rule of law. 27
Sri Lanka’s regulatory quality score fell from -0.10 in 2006 to -0.28 in 2008, which compares
unfavorably with the Philippines’ score (-0.05) and Thailand’s (0.26) (Figure 3-3). Sri Lanka’s
score reflects the fact that its somewhat confusing and opaque regulatory system raises the cost of
doing business.
26 Sally, Razeen, Sri Lanka at the Crossroads, Far Eastern Economic Review, July/August 2009, p. 34.
27 Justice in Retreat, International Bar Association Human Rights Institute Report, May 2009.

20 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
Figure 3-2
Rule of Law Index
There are concerns about the government’s commitment to rule of
law.
Comparisons to other countries, most recent year
-2.5 (Very poor performance) - +2.5 (Excellent performance)
-0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6
Expected value and margin of error
-0.69
-0.43
-0.49
-0.01
S ri L a nka
LMI-As ia
LMI
P hilippines
-0.03
Thailand
SOURCE: World Bank Institute CAS code: 22P3
Figure 3-3
Regulatory Quality Index
Opaque regulation increases business costs.
Comparisons to other countries, most recent year
-2.5 (Very poor performance) - +2.5 (Excellent performance)
-0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5
-0.44
-0.28 S ri L a nka
-0.29 LMI-As ia
LMI
P hilippines
-0.05
Thailand
SOURCE: World Bank Institute CAS code: 22P4
0.1
0.26
Now that the civil conflict has ended, more attention needs to be paid to regional differences in
the institutional environment for doing business. Donors should promote legal and regulatory

P RIVATE S ECTOR ENABLING E NVIRONMENT 21
systems that make it easier to establish and operate small and medium-sized businesses,
especially in the impoverished north and east. Since the World Bank Office in Sri Lanka reports
that rural entrepreneurs mentioned that laws and regulations are sometimes improperly
implemented, special efforts should be made to collect subnational business indicators to guide
and report on donor-supported reforms in disadvantaged regions. 28
FINANCIAL SECTOR
A sound and efficient financial sector is a key to mobilizing saving, fostering productive
investment, and improving risk management. State-owned institutions dominate Sri Lanka’s
financial system. State banks hold nearly half of banking assets and nearly a quarter of financial
sector assets. Government debt represents the largest single exposure of the financial system,
accounting for approximately a quarter of bank assets (loans and investments) and more than 90
percent of investments of the pension and insurance institutions. 29
Banks are the leading part of Sri Lanka’s financial sector; their assets are approximately twothirds
of financial sector assets. The two largest commercial banks are state-owned. In addition to
other commercial banks are many finance companies and leasing companies. The Employee
Provident Fund, comprising nearly 15 percent of financial sector assets and managed by the
Central Bank of Sri Lanka, dominates the pensions sector. The vast majority of pension fund
assets are held as government debt. Insurance is relatively underdeveloped in Sri Lanka;
premiums are a mere 1.5 percent of GDP.
Sri Lanka’s financial system is relatively underdeveloped compared to other lower middleincome
countries. For example, its ratio of broad money (currency plus bank deposits) to GDP
declined from 37.9 percent in 2006 to 34.6 percent in 2008. By this measure, monetary deepening
in Sri Lanka is below the expected value (59.7 percent) and the LMI-Asia median (45.4 percent)
and less than in the Philippines (52.9 percent) and considerably less than in Thailand (99.7
percent) (2007).
Growth in domestic credit to the private sector has also decelerating, going from 34 percent in
2006 to 28.9 percent in 2008. On this measure Sri Lanka underperforms compared to its expected
value (39.4 percent), LMI-Asia (30.5 percent), and Thailand (92.4 percent) (2007), but is on par
with the Philippines (28.8 percent) (Figure 3-4). This decline is attributable to high real interest
rates that resulted from tighter monetary policy in 2008 and bank lending for deficit financing and
government-owned corporations that crowds out lending for private businesses. And as global
demand contracted in late 2008 and into 2009, so did demand for many of Sri Lanka’s exports
and tourism as well as private demand for credit as businesses saw orders fall and became
reluctant to undertake new investments.
28 World Bank Sri Lank Office Website, Governance in Sri Lanka, 2009.
29 International Monetary Fund, Sri Lanka Financial System Stability Assessment Update, November
2007, p. 10.

22 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
Figure 3-4
Domestic Credit to Private Sector, Percent GDP
Slow growth and a credit crunch have reduced domestic credit to the private sector.
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Time Series Comparisons to other countries, most recent year
2004 2005 2006 2007 2008
Year Value
2004 30.6
2005 32.9
2006 34.0
2007 33.3
2008 28.9
Summary for 2004- 2008
Five year average 31.9
Trend growth rate -1.0
Percent GDP
100
90
80
70
60
50
40
30
20
10
0
39.4
Expected value and margin of error
28.9 30.5 29.6 28.8 92.4
S ri L a nka LMI-As ia LMI P hilippines Thailand
Sri Lanka Global
Standing
Highest-five average
3
196
LKA
Lowest-five average
SOURCE: IMF International Financial Statistics and World Development Indicators 2009 CAS code: 23P1
Commercial banks raised nominal interest rates on loans and deposits in the high inflation
environment of 2008. With inflation in 2009 under control at 4 percent to 6 percent, banks should
start reducing interest rates, although this will take some time as term deposits and CDs offering
higher rates last year are still on the books. Real interest rates, which were negative for most of
2008, became positive in 2009 and are currently high.
Other credit services in addition to bank credit include leasing. Under a leasing arrangement, a
lessee may make a prepayment and then enter into a pay-as-you go agreement, thereby reducing
the burden of paying the entire amount for the use of a good or service upfront. Leasing
arrangements can be very promising for small and medium-sized businesses that usually cannot
borrow from commercial banks. Donors who are helping to develop such financial services
should continue to do so and explore other means for making credit available to rural and small
investors.
Stock market capitalization is another indicator of financial development. In 2007, Sri Lanka’s
ratio of stock market capitalization to GDP was 23.4 percent, above the expected value (8.9
percent), but significantly below the LMI-Asia median ratio (44 percent) and ratios in the
Philippines (71.7 percent) and Thailand (79.9 percent). Like stock markets worldwide, Sri
Lanka’s was increasingly volatile in 2008 and 2009. By August 2009, however, the Colombo All
Share Index had nearly returned to its 2007 pre-crisis level, no doubt a reaction in large part to the
positive news of the end of conflict.

P RIVATE S ECTOR ENABLING E NVIRONMENT 23
EXTERNAL SECTOR
Fundamental changes in international commerce and finance, including reduced transport costs,
advances in telecommunications technology, and lower policy barriers, have fueled a rapid
increase in global integration in the past 25 years. The international flow of goods and services,
capital, technology, ideas, and people offers great opportunities for Sri Lanka to boost growth and
reduce poverty by stimulating productivity and efficiency, providing access to new markets and
ideas, and expanding the range of consumer choice. At the same time, globalization creates new
challenges, including the need for reforms to take full advantage of international markets, and
cost-effective approaches to cope with the resulting adjustment costs and regional imbalances.
International Trade and Current Account Balance
Three decades after discarding the closed-economy model of development, Sri Lanka is still
much less active in trade than many similar countries. In 2008, trade flows equaled 64.7 percent
of GDP. This is well below the normal range for a country with Sri Lanka’s characteristics as
estimated by the regression benchmark of 119.6 percent. It is also far lower than the figures for
Thailand (139 percent) and the Philippines (84.8 percent).
The World Bank’s Doing Business in 2009 ranked Sri Lanka 66 among 181 countries for ease of
trading across borders, a big improvement from previous years when Sri Lanka was closer to 100,
although still behind comparator countries (see Business Environment section).
The country has performed moderately well in export growth, which averaged 8.7 percent
between 2006-2008, but high export concentration in tea, garments, and rubber comprise make it
particularly vulnerable to the global economic crisis. Thus, the trade deficit grew by 61 percent in
2008 to US$5.9 billion and the current account deficit more than doubled to 9.4 percent of GDP
from 4.2 percent of GDP in 2007 (see Figure 3-5). The current account deficit was much higher
than regional averages and the comparator countries: the LMI-Asia median amounted to a surplus
of 0.2 percent of GDP and the LMI median had a deficit of 3.1 percent, while the Philippines had
a surplus of 1.0 percent and Thailand a deficit of 0.1 percent.
Export growth declined from 10.7 percent in 2007 to 7.7 percent in 2008 as sales fell in the
United States and EU, the main markets for Sri Lankan exports. Growth in apparel exports, for
example, slowed from an estimated 7 percent in 2007 to 5 percent in 2008. 30 On a positive note,
the Generalized System of Preferences for apparel as well as concessions from the European
Union (EU) were conditionally extended for three years. Employing more than one million
people and accounting for more than 50 percent of export earnings, the labor-intensive apparel
industry is very important to Sri Lanka. 31
Sri Lanka is one of world largest tea producers and tea exports are Sri Lanka’s third largest
source of foreign exchange. Earnings from this subsector exceeded $1 billion for the first time in
2007. Demand for tea remained strong in 2008 despite the recession, indicating a relatively
30 Asian Development Bank, “Sri Lanka” 2009 Outlook.
31 Sally, Razeen, “Sri Lanka at the Crossroads,” Far Eastern Economic Review, July/August 2009.

24 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
inelastic demand for this product. Unfortunately, falling domestic production resulted in falling
export revenues in the first half of 2009.
Figure 3-5
Current Account Balance, percent GDP
F altering world demand and high oil prices widened the trade deficit.
15.0
10.0
5.0
0.0
-5.0
-10.0
-15.0
Time Series Comparisons to other countries, most recent year
2004 2005 2006 2007 2008
Year Value
2004 -3.1
2005 -2.7
2006 -5.3
2007 -4.2
2008 -9.4
Summary for 2004-2008
Five year average -4.9
Trend growth rate -26.6
Percent GDP
2
0
-2
-4
-6
-8
-10
-12
-14
-16
-18
S ri L a nka LMI-As ia LMI P hilippines Thailand
-9.4
-11.6
0.2
-3.1
1.0
Expected value and margin of error
-0.1
Sri Lanka Global
Standing
Highest-five average
-27.4
29.8
LKA
Lowest-five average
SOURCE: IMF CAS code: 24P2
Tourism is the country’s fourth largest source of foreign exchange earnings and, according to the
World Travel and Tourism Council, employs about 374,000 people. Tourist arrivals for 2008—
about 438,475—declined by 11.2 percent from 2007. The global recession may limit the number
of Western tourists arriving in Sri Lanka for the next couple of years, but more could arrive from
India and the Middle East. The government, in fact, seems to be targeting these growing
economies, as well as China, for their tourism potential. 32
The value of Sri Lanka’s imports increased in 2008, largely as a result of the higher import prices
for oil, but also because of increased imports of fertilizer and food. Growth of trade in services
also slowed from 14.2 percent in 2007 to 13.3 percent in 2008, contributing to the overall trade
deficit.
Given falling fuel prices, import growth should slow and the trade deficit should decline
significantly in 2009. International tea prices have risen recently to near the peak levels of last
32 Business Monitor International, Sri Lanka Tourism Report, Q1 2009: Including 5-year industry
forecasts (March 2009). The report mentions that Sri Lankan Airlines now has Chinese-speaking personnel
on each flight to Beijing, as well as Chinese-speaking ground staff to help passengers in transit to
Bandaranaike International Airport. And in January 2009, Sri Lanka signed an MOU with the government
of Gujarat province in India to promote tourism.

P RIVATE S ECTOR ENABLING E NVIRONMENT 25
year’s commodity boom. In addition, remittances have risen steadily from US$1.56 billion in
2004 to US$2.9 billion in 200833 as the diaspora in the Middle East faithfully send earnings back
to families in Sri Lanka. Remittances for the first six months of 2009 were up slightly from the
same period last year, from US$1.50 billion to US$1.58 billion, and this will help to offset the
deficit in the trade account.
How much rebound there will be in current account balance for 2009 remains to be seen.
Estimates range from 4 percent to 5 percent of GDP to the government’s much more optimistic
estimate of 2.7 percent.
Foreign Investment, External Assistance, and International
Reserves
Foreign direct investment (FDI) can boost productivity and growth by transferring technology,
developing human capital, and enhancing competition. The flow of FDI into Sri Lanka has been
growing slowly but steadily and reached nearly 2 percent of GDP in 2008. Since the opening up
of the economy in the1970s, the government has established export processing zones and offered
incentives offered to attract FDI for industrial development. The government has also granted tax
exemptions to attract foreign investors, but began rationalizing exemptions in 2008 in order to
recover revenue. Outside of the export processing zones, foreign investment is either partially or
wholly restricted in many of Sri Lanka’s sectors. 34
While foreign investment as percent of GDP remains low compared to Thailand (3.9 percent), it
was almost at par with the Philippines (2 percent) in 2008. Now that the “war on terror” has
ended for Sri Lanka, foreign investors are very optimistic about growth prospects and private
investment is starting to flow in, especially as opportunities for rebuilding open up in the north
and east. In just May 2009 alone, US$123 million in foreign reserves entered the country as a
result of the ending of the long-running conflict. Calamander Group Pte, an investment firm
based in Singapore, announced in June that it will create the first private equity fund focused on
Sri Lanka. Calamander plans to invest between $US50–US$70 million in the island nation’s
rubber, tea, timber, and other businesses in the next year and a half. 35
External Borrowing
Sri Lanka’s total external debt of US$15.1 billion and was 37 percent of GDP in 2008. The ratio
of external debt service to export earnings has been increasing in recent years, from 7.9 percent in
2005 to an estimated 15 percent in 2008. 36 Sri Lanka has been turning increasingly to foreign
commercial borrowing to finance its budget deficit, the share of which, in total foreign debt, rose
33 Sri Lanka Central Bank Statistical Appendix. Note that the 2008 figure was provisional in this
document.
34 Business Monitor International, Sri Lanka Tourism Report, Q1 2009: Including 5-year industry
forecasts (March 2009).
35 Asia Monitor, 2009 Growth Forecast Still on Track: Sri Lanka Economic Outlook, August 2009
source: www.asia-monitor.com.
36 Sri Lanka Central Bank Statistical Appendix. Table 4.

26 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
from 5 percent in 2003 to 13 percent in 2007. 37 The country floated its first sovereign bond in
2007, a US$500 million five-year issue with a high interest rate (8.25 percent). But with the onset
of the global financial crisis in late 2008, foreign investors who had bought Sri Lankan debt sold
off rupee-denominated securities, causing a balance of payments crisis in the country. Given
renewed confidence in the country since the defeat of the LTTE, the government is considering
issuing another sovereign bond, with the hope of obtaining a lower rate of interest.
Exchange Rate and International Reserves
The CBSL has been maintaining a managed float of the rupee and responded to the sudden
withdrawal of foreign monies by intervening heavily in the foreign exchange market to keep the
rupee from depreciating further against the U.S. dollar. This nearly resulted in a financial crisis as
Sri Lanka’s foreign exchange reserves plunged by US$800 million, more than 30 percent,
between August and November 2008. The reserves stood at $1.7 billion in November 2008—
equivalent to 1.5 months of imports, down from $3.4 billion in early August.
With the ending of the conflict and external monies flowing in, foreign exchange reserves have
been built back up and were at US$2.2 billion in August 2009. The IMF loan will also be used
primarily for stabilizing the balance of payments.
Figure 3-6
Foreign Exchange Reserves, $US billions
F oreign exchange reserves are stabilizing after the drop in 2008.
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Dec-07
Feb-08
Time Series
Apr-08
Jun-08
Aug-08
Oct-08
Dec-08
Feb-09
Apr-09
Jun-09
Aug-09
Year Value
Dec-07 3.5
Aug-08 3.4
Dec-08 1.7
Mar-09 1.3
Aug-09 2.2
SOURCE: Asian Development Bank 2009 Outlook CAS code: N/A
The CBSL’s intervention to prevent depreciation—it had targeted a goal of 108 rupees to the U.S.
dollar—was untenable because of the shortage of foreign reserves and the currency has been
depreciating in 2009. In August, the rate was about 114 rupees to the U.S. dollar. If interest rates
continue to decline, the nominal exchange rate may drop further. 38
37 Asian Development Bank, “Sri Lanka” 2009 Outlook.
38 The IMF package is predicting an exchange rate of $118/US$1 by 2010.

P RIVATE S ECTOR ENABLING E NVIRONMENT 27
In 2008 the Sri Lankan rupee depreciated less than inflation accelerated, resulting in a real
appreciation of the exchange rate. But starting in 2009 the rupee depreciated more than inflation
rose, resulting in a real depreciation of the exchange rate. Export producers and those who
produce goods in competition with imports have benefited, while importers and sectors with a
high import content have suffered.
ECONOMIC INFRASTRUCTURE
Reliable physical infrastructure—for transportation, communications, power, and information
technology—is necessary to improve competitiveness and expand productive capacity. Sri
Lanka’s poor quality of infrastructure is a serious deterrent to investment. The WEF compiles an
annual index of infrastructure based on a survey of executive opinion in each country. For 2008,
Sri Lanka received a rating of 3.8 on a scale of 1 (poor) to 7 (excellent), which is an increase from
the 2007 rating of 3.3. This rating is above the global LMI and LMI-Asia medians of 3.0, but the
lags well behind Thailand (4.8).
Transportation infrastructure is crucial for domestic and international trade. Sri Lanka’s rail
system, which once dominated transportation, has suffered from inadequate maintenance and two
decades of conflict. Poor track condition, outdated signaling and communications systems, and an
insufficient number of locomotives have all led to significant delays in train schedules and even
to derailments. As a result, the highly congested national roads are now the primary means of
moving commercial goods and the general public.
In 2006, approximately 81 percent of Sri Lanka’s 91,907 kilometers road network was paved. 39 A
major constraint on economic activities and development outside the Colombo Metropolitan area,
however, is the poor condition of the inadequately maintained pavement. Through its Road Sector
Assistance Project, the World Bank will be providing a US$100 million credit to the Sri Lankan
government to improve roads. The project covers a network of 630 km of national roads. 40 Many
roads linking the northeast to the rest of the country were closed for years during the conflict and
have recently been reopened for public use. Rehabilitation of roads and infrastructure in the north
will be a first step in rebuilding.
Electric power is also critical to manufacturing and commerce for the domestic market and for
export. On the WEF index of electricity infrastructure quality, Sri Lanka’s rating of 4.6 is below
Thailand’s rating of 5.5, but in line with the expected value of 4.5 and exceeds the LMI-Asia
median of 3.8. Still, according to a 2004 Investment Climate Assessment (ICA) by the Asia
Development Bank and the World Bank, the high cost and erratic quality of electricity in Sri
Lanka is the top constraint on urban manufacturing there.
Information and communication infrastructure are now just as important as traditional
infrastructure and electricity grids. Several indicators show that Sri Lanka lags behind its
comparators in such infrastructure. Only 5.7 people per 100 were internet users in 2008, fewer
than the global LMI median (8.6) and than in the Philippines (6) and Thailand (20) (Figure 3-7).
39 World Bank. Sri Lanka: Transport at a Glance, 2007.
40 World Bank. Sri Lanka: Road Sector Assistance Project.

28 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
Telephone density appears to be rising rapidly, going from 16.5 fixed and mobile telephones per
100 people in 2005 to 72.4 in 2008. As this is a worldwide phenomenon, the Philippines and
Thailand outperform Sri Lanka with 79.7 line and 89.6 lines per 100 people. 41
Figure 3-7
Internet Users, per 100 people
Internet users are increasing consistently but remain below benchmarks and expected value.
6.0
5.0
4.0
3.0
2.0
1.0
0.0
Time Series Comparisons to other countries, most recent year
2004 2005 2006 2007 2008
Year Value
2004 1.4
2005 1.8
2006 2.5
2007 3.9
2008 5.7
Summary for 2004-2008
Five year average 3.1
Trend growth rate 35.8
Us e rs
35
30
25
20
15
10
5
0
25.9
Expected value and margin of error
5.7 4.6 8.6 6.0 20.0
S ri L a nka LMI-As ia LMI P hilippines Thailand
Sri Lanka Global
Standing
Highest-five average
0.2
82.6
LKA
Lowest-five average
SOURCE: International Telecommunications Union CAS code: 25P1
Low quality infrastructure in Sri Lanka deters investment, undermines the competitiveness of
existing businesses, retards job creation, and generally impedes growth, particularly outside the
Western Province. Donor assistance for the establishment of public-private partnerships and to
encourage private sector participation in upgrading physical infrastructure, especially electricity
and transport, can be a catalyst for rapid growth and help reduce regional imbalances.
SCIENCE AND TECHNOLOGY
Science and technology are vital to a dynamic business environment and are a driving force
behind productivity and competitiveness. Even for LMI countries such as Sri Lanka,
transformational development depends on acquiring and adapting technology from the global
economy. Lack of capacity to access and use technology prevents an economy from benefiting
from globalization.
Unfortunately, very few international indicators can be used to judge performance in this area for
low- and lower-middle-income countries. From the limited information that is available, it
appears that science and technology capability in Sri Lanka is above average for its level of
development. For example, the annual WEF survey of executive perceptions of country
41 International Telecommunications Union.

P RIVATE S ECTOR ENABLING E NVIRONMENT 29
competitiveness includes a rating for the availability of scientists and engineers. For 2008, Sri
Lanka received a score of 4.9 (on an ascending scale of 1 to 7), better than all comparators and
above the expected value of 3.2. Moreover, Sri Lanka’s score is consistently improving.
Another indicator is the WEF’s index of FDI Technology Transfer, which gauges the degree to
which FDI brings new technology into an economy. Sri Lanka’s score of 5.1 (on the same
ascending scale of 1 to 7) is above the expected value of 4.1 for a country with Sri Lanka’s
characteristics and on par with comparator economies the Philippines, Thailand, and the LMI-
Asia median score.
Progress in science and technology is also influenced by intellectual property rights (IPR); weak
protection of intellectual property can discourage investment involving innovative or proprietary
technologies. Sri Lanka’s score of 3.7 on the WEF’s IPR index is just below Thailand’s score of
3.9. Sri Lanka’s performance on this indicator has also shown consistent improvement since
2006.
Investing in science and technology education linked to productive employment is one of the best
ways to drive growth. Donors would do well to assist with workforce development and IPR
reform.

4. Pro-Poor Growth
Environment
Rapid growth is the most powerful and dependable instrument for poverty reduction, but the link
from growth to poverty reduction is not mechanical. In some circumstances, income growth for
poor households exceeds the overall rise in per capita income, in others the poor are left far
behind. A pro-poor growth environment stems from policies and institutions that improve
opportunities and capabilities for the poor while reducing their vulnerabilities. Pro-poor growth is
associated with investment in primary health and education, the creation of jobs and income
opportunities, the development of skills, microfinance, agricultural development, and gender
equality. This section focuses on four of these issues: health, education, employment and the
workforce, and agricultural development.
HEALTH
The provision of basic health services is a major form of capital investment and a significant
determinant of growth and poverty reduction. Although health programs do not fall under the
purview of the EGAT bureau, an understanding of health conditions can influence the design of
economic growth interventions.
Life expectancy at birth is commonly regarded as the best overall indicator of the health of a
population. By this measure Sri Lanka’s health system is performing well. In 2007 life
expectancy was 72.4 years, significantly above the LMI-Asia median (66.5) and the LMI median
(69.2) and even above life expectancy in the Philippines (71.7) and Thailand (70.6).
Sri Lanka also fares well on other health indicators, such as maternal mortality. In 2005, its
maternal mortality rate was an estimated 58 maternal deaths per 100,000 live births, which is less
than half of all benchmarks. 42 The rate is low as 98.5 percent of births (2007) are attended by a
skilled health professional, on par with Thailand’s 97 percent (2006) and much higher than the
Philippines (only 60 percent in 2003).
In several critical areas, however, there are deficiencies. For example, the child malnutrition rate
in Sri Lanka was estimated at 21.6 percent in 2006/07. Although this shows improvement from
42 2003 data from the MDG Indicator of Sri Lanka Report, lists a rate of 19.7 percent. The 2005 WDI
figure was used in the text for benchmarking purposes.

32 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
29.4 percent in 2000, it is significantly higher than in Thailand (7.0). 43 Children living on estates
suffer the highest level of malnutrition (29.7 percent), compared to living in rural areas (21.7
percent) or urban areas (16.6 percent). 44 This basic deficiency raises serious concerns about longterm
growth prospects, because child malnutrition today can impair the health and productivity of
the next generation of workers. Statistics indicate that half of Sri Lankans lacks adequate dietary
energy consumption (see discussion of Poverty and Inequality in section 2).
Access to clean water is another serious concern. In 2006 only 82 percent of the population in Sri
Lanka had access to an improved water source, compared to 93 percent in the Philippines and 98
percent in Thailand (Figure 4-1). And 57.8 percent of Sri Lankans in estate households lack
access to clean water. Access to improved sanitation is better. An estimated 86 percent of the
population had access to improved sanitation in 2006— exceeding the expected value of 85.8
percent and just slightly less than in Thailand (96.0 percent).
Figure 4-1
Access to Improved Water
There is less access to clean water than in country comparators.
Percent
100
80
60
40
20
0
Comparisons to other countries, most recent year
82.0
82.0
84.0
93.0
98.0
S ri L a nka LMI-As ia LMI P hilippines Thailand
SOURCE: World Development Indicators 2009 CAS code: 31S2
These health problems are clearly associated with the poverty and inequality discussed earlier.
Government resources devoted to health have fallen in recent years, from 2 percent of GDP in
2006 to 1.7 percent in 2008. This is somewhat better than in the Philippines (1.3 percent), but
significantly less than the LMI-median (2.6 percent) and Thailand and LMI-Asia (2.3 percent).
More government and donor support will be required to reduce regional disparities on health
indicators and should be understood as an essential investment in human capital.
43 Current data for other comparators were not available.
44 MDG Indicators for Sri Lanka, 2008, 22.

P RO- P OOR G ROWTH E NVIRONMENT 33
EDUCATION
Investment in education is another cornerstone of economic growth and development. In addition,
universal access to education can diminish grievances by reducing historic inequalities and
fostering economic opportunity. Sri Lanka’s strong commitment to education is evident in its
high net primary school enrollment rate of 97.5 percent (2006/07). This is well above the
expected value of 93.2 percent and outperforms all comparators. Regional disparities are also
low, with net primary school enrollment rates in all provinces between 96 and 99 percent. 45
The primary completion rate, however, was just 88.2 percent in 2006/07, lower than the rate in
the Philippines (94 percent) and the global LMI-median (95.3 percent). The completion rate
among estate households was 69.5 percent, well below rates for urban (87 percent) and rural
households (89 percent). This high dropout rate for estate households is symptomatic of the
poverty in this segment of the population.
Education quality is difficult to measure. At the primary level, a crude but common proxy is the
pupil–teacher ratio, with fewer students per teacher being preferable. In 2006, there were 25.3
students per teacher in Sri Lanka, which is better than regional and income-group benchmarks as
well as the ratio in the Philippines (34.6) but higher than in Thailand (17.7).
The country’s educational performance has been achieved with a very little state expenditure on
primary education. In 2006 (latest year available) spending on primary education amounted to
just 0.7 percent of GDP, compared to the Philippines (1.5 percent) and Thailand (1.3 percent).
More investment is needed to maintain enrollment rates and raise the retention rate. Doing so will
expand economic opportunities for economic growth and poverty reduction.
EMPLOYMENT AND WORKFORCE
Between 2006 and 2008, Sri Lanka’s labor force grew at an average rate of more than 2.2 percent
compared to a population growth rate of 1.0 percent. About 9 million people were active in the
labor force in 2008, with an overall labor force participation rate of 58.6 percent. While this has
increased considerably since 2004 when it was 48.6 percent, it is still lower than the LMI-Asia
median of 64.7 percent and the LMI median of 63 percent. Labor force participation rates are also
higher in the Philippines (65.1 percent) and Thailand (72.8 percent).
The country has a well-educated and relatively cheap labor force. Sri Lankan workers are the
most educated in South Asia: 90 percent can read and write and about 10 percent have received
tertiary education. 46
Sri Lanka’s official unemployment rate in 2008 was 5.2 percent, although the official data
exclude the northern and eastern provinces. Unemployment was much higher among females (8
45 MDG Indicators of Sri Lanka, 2008, 84. Data exclude Northern Province and Trincomalee district in
the Eastern province.
46 Business Monitor International, Sri Lanka Tourism Report, Q1 2009: Including 5-year industry
forecasts (March 2009).

34 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
percent) than males (3.6 percent). 47 The labor market is fairly rigid. According to the Doing
Business 2009, the cost of firing a redundant worker measured in weeks is equivalent to 3.25
years, much higher than in the Philippines (1.75 years) and Thailand (1 year). Dealing with these
rigidities is very difficult, however, given the political clout of Sri Lanka’s numerous labor
unions.
The country has a huge public sector, with about 1.25 million people—or nearly 14 percent of the
workforce—holding government jobs. New opportunities in the private sector that accompany
rising private investment, foreign and domestic, should reduce the burden on state employment.
AGRICULTURE
With 31.3 percent of the labor force generating 13.4 percent of value added in Sri Lanka, labor
productivity in agriculture is low compared to manufacturing or services. In 2008, value added
per worker in agriculture was US$705 in constant 2000 prices—more than the LMI-Asia median
(US$595) and value added in Thailand (US$615)—but less than in the Philippines (US$1,097).
Performance on average yield indicators, however, is much better. The FAO reports that the
average cereal yield in 2007 was 3,822 kilograms per hectare, exceeding the yield for LMI-Asia
(3,164), the Philippines (3,261), and Thailand (2,752) (Figure 4-2). That the government
subsidizes fertilizer in Sri Lanka is evident in statistics on fertilizer consumption: in 2005 (latest
year of comparable data) consumption as measured by the quantity of plant nutrients per unit of
arable land was 3,071 grams per hectare, high compared to consumption in the Philippines
(1,310) and Thailand (1,207). This result is not surprising given the government’s policy of selfsufficiency
in rice production. Unfortunately, this policy combined with restrictions on imports—
including a 20 percent tariff on rice imports—and price supports, all drive up prices.
47 Sri Lanka Central Bank Statistical Appendix. Table 1.

P RO- P OOR G ROWTH E NVIRONMENT 35
Figure 4-2
Cereal Yield, kilograms per hectare
Iimport restrictions, price supports, and fertilizer subsidies result in high rice yields.
5,000
4,000
3,000
2,000
1,000
0
Time Series Comparisons to other countries, most recent year
2003 2004 2005 2006 2007
Year Value
2003 3,283
2004 3,564
2005 3,467
2006 3,619
2007 3,822
Summary for 2003-2007
Five year average 3,551
Trend growth rate 3.2
Kilog ra ms pe r he c ta re
4,500
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
2,107
Expected value and margin of error
3,822 3,164 1,939 3,261 2,752
S ri L a nka LMI-As ia LMI P hilippines Thailand
SOURCE: World Development Indicators, 2008 CAS code: 34P2
The self-sufficiency policy for rice erodes incentives for farmers to produce higher-value crops
and saddles the government budget with expenditures that prevent spending on other items.
Meanwhile, poor irrigation design, water management, and system maintenance have led to
insufficient paddy water coverage. Rice production is therefore variable and vulnerable given the
increasing reliance on rainfall.
The WEF’s index of Agricultural Policy Cost is scaled from 1 (excessively burdensome) to 7
(well balanced). In 2008 Sri Lanka scored its expected value of 3.9, close to the score for LMI-
Asia and the Philippines (3.8) and Thailand’s score of 4.1. As the index is based on a survey of
the opinions of the private sector, especially farmers and agribusiness, it shows that government
policy is seen as impeding agricultural development. This suggests that the government’s role in
agriculture should be reduced and market forces allowed more scope to ensure that producers
have the right information and incentives to diversify into higher value-added crops. The World
Bank also cites the need to introduce improved technologies and seed, liberalize phytosanitary
regulations to encourage private sector participation, strengthen agricultural research and
extension services, and phase out tariff protection. 48
With the government holding more than 80 percent of land held as “crown lands,” land tenure
and land market policies in Sri Lanka may need some reform if economic development is to
gather momentum. Legislation enacted in 1972 was intended to abolish large private holdings and
48 World Bank, Sri Lanka: Priorities for Agriculture and Rural Development, 2009.

36 S RI L ANKA E CONOMIC P ERFORMANCE A SSESSMENT
encourage the transfer of land to near-landless or landless peasants, 49 but has resulted in
increasing the amount of land under the control of government and state agencies or cooperatives.
The government’s ideological tenet that the state should control land decisions permeates land
policies. Land grants, for example, prohibit farmers from selling land. This legacy explains why
there has been little or no discussion of land privatization and why the Board of Investments
rarely approves agribusiness projects. The legal and regulatory basis for leasing governmentowned
land is unclear, and the government does not openly acknowledge that such lands should
be put to productive use.
Given Sri Lanka’s low rate of urbanization and high incidence of rural poverty, policies to
increase agricultural productivity are sorely needed. The cessation of conflict presents an
excellent opportunity for adjusting policies and raising productivity. For example, seafood
exports increased in 2009 after military fishing restrictions were lifted. 50 Agriculture
development could benefit from donor assistance with marketing and processing and assistance
that encourages the production of value-added output. Donor assistance should also aim to
improve rural transportation infrastructure and thus curb production losses. Assistance to improve
land titling would have multiple benefits. It would facilitate the resettlement of Tamils and the
use of land as lending collateral. Assistance to reduce trade barriers would help agricultural
producers get the pricing information they need to make sound decisions on what crops to invest
in.
49 For example, The Land Development Ordinance of 1935 restricted transfer of crown land to small
holder peasants; the Land Reform Law of 1972 imposed a ceiling on private holdings above 20 hectares
and sought to distribute land above this ceiling to benefit the landless.
50 Sri Lanka Daily News, August 12, 2009.

Appendix A. CAS Methodology
CRITERIA FOR SELECTING INDICATORS
The economic performance evaluation in this report balances the need for broad coverage and
diagnostic value with the requirements of brevity and clarity. The analysis covers 15 economic
growth–related topics, and just over 100 variables. For the sake of brevity, the write-up in the text
highlights issues for which the “dashboard lights” appear to be signaling problems, which suggest
possible priorities for USAID intervention. The table below provides a full list of indicators
examined for this report. The data supplement in Appendix B contains the complete data set for
Sri Lanka including data for the benchmark comparisons, and technical notes for every indicator.
For each topic, the analysis begins with a screening of primary performance indicators. These
Level I indicators are selected to answer the question: Is the country performing well or not in
this area? The set of primary indicators also includes descriptive variables such as per capita
income, the poverty head count, and the age dependency rate.
When Level I indicators suggest weak performance, we review a limited set of diagnostic
supporting indicators. These Level II indicators provide additional details, or shed light on why
the primary indicators may be weak. For example, if economic growth is poor, one can examine
data on investment and productivity as diagnostic indicators. If a country performs poorly on
educational achievement, as measured by the youth literacy rate, one can examine determinants
such as expenditure on primary education, and the pupil–teacher ratio. 1
Indicators have been selected on the basis of the following criteria. Each must be accessible
through USAID’s Economic and Social Database or convenient public sources, particularly on
the Internet. They should be available for a large number of countries, including most USAID
client states, to support the benchmarking analysis. The data should be sufficiently timely to
support an assessment of country performance that is suitable for strategic planning purposes.
Data quality is another consideration. For example, subjective survey responses are used only
when actual measurements are not available. Aside from a few descriptive variables, the
indicators must also be useful for diagnostic purposes. Preference is given to measures that are
widely used, such as Millennium Development Goal indicators, or evaluation data used by the
Millennium Challenge Corporation. Finally, an effort has been made to minimize redundancy. If
two indicators provide similar information, preference is given to one that is simplest to
understand, or most widely used. For example, both the Gini coefficient and the share of income
1 Deeper analysis of the topic using more detailed data (Level III) is beyond the scope of this series.

A - 2 A PPENDIX A
accruing to the poorest 20 percent of households can be used to gauge income inequality. We use
the income share because it is simpler and more sensitive to changes.
BENCHMARKING METHODOLOGY
Comparative benchmarking is the main tool used to evaluate each indicator. The analysis draws
on several criteria, rather than a single mechanical rule. The starting point is a comparison of
performance in Sri Lanka relative to the average for countries in the same income group and
region —in this case, lower-middle-income countries in Asia. 2 For added perspective, three other
comparisons are examined: (1) the global average for this income group; (2) respective values for
two comparator countries approved by the Sri Lanka mission; and (3) the average for the five
best- and five worst-performing countries globally. Most comparisons are framed in terms of
values for the latest year of data from available sources. Five-year trends are also taken into
account when this information sheds light on the performance assessment. 3
For selected variables, a second source of benchmark values uses statistical regression analysis to
establish an expected value for the indicator, controlling for income and regional effects. 4 This
approach has three advantages. First, the benchmark is customized to Sri Lanka specific level of
income. Second, the comparison does not depend on the exact choice of reference group. Third,
the methodology allows the quantification of the margin of error and establishment of a “normal
band” for a country with Sri Lanka’s characteristics. An observed value falling outside this band
on the side of poor performance signals a serious problem. 5
Finally, where relevant, Sri Lanka’s performance is weighed against absolute standards. For
example, a corruption perception index below 3.0 is a sign of serious economic governance
problems, regardless of the regional comparisons or regression result.
2 Income groups as defined by the World Bank for 2008. In this report, the average is defined in terms of
the median so that values are not distorted by outliers.
3 The five-year trends are computed by fitting a log-linear regression line through the data points. The
alternative of computing average growth from the end points produces aberrant results when one or both of
those points diverges from the underlying trend.
4 This is a cross-sectional OLS regression using data for all developing countries. For any indicator, Y,
the regression equation takes the form: Y (or ln Y, as relevant) = a + b * ln PCI + c * Region + error –
where PCI is per capita income in PPP$, and Region is a set of 0-1 dummy variables indicating the region
in which each country is located. When estimates are obtained for the parameters a, b, and c, the predicted
value for the Sri Lanka is computed by plugging in Sri Lanka-specific values for PCI and Region. Where
applicable, the regression also controls for population size and petroleum exports (as a percentage of GDP).
5 This report uses a margin of error of 0.68 times the standard error of estimate (adjusted for
heteroskedasticity, where appropriate). With this value, 25 percent of the observations should fall outside
the normal range on the side of poor performance (and 25 percent on the side of good performance). Some
regressions produce a very large standard error, giving a “normal band” that is too wide to provide a
discerning test of good or bad performance.

CAS M ETHODOLOGY A - 3
STANDARD CAS INDICATORS
Indicator Level MDG, MCA, or EcGov a
Statistical Capacity Indicator I EcGov
Growth Performance
Per capita GDP, in purchasing power parity Dollars I
Per capita GDP, in current US Dollars I
Real GDP Growth I
Growth of labor productivity II
Investment Productivity, incremental capital-output ratio (ICOR) II
Gross fixed investment, percent GDP II
Gross fixed private investment, percent GDP II
Poverty and Inequality
Human poverty index (0 for excellent to 100 for poor) I
Income-share, poorest 20 percent I
Population living on less than $1.25 PPP per day I MDG
Poverty Headcount, by national poverty line I MDG
PRSP Status I EcGov
Population below minimum dietary energy consumption II MDG
Economic Structure
Employment or labor force structure I
Output structure I
Demography and Environment
Adult literacy rate I
Youth dependency rate/ Elderly dependency rate I
Environmental performance index (0 for poor to 100 for excellent) I
Population size and growth I
Percent of population living in urban areas I
Resource depletion, percent GNI I
Gender
Primary completion rate, male, female I MCA
Gross enrollment rate, all levels, male, female I MDG
Life expectancy at birth, male, female I
Labor force participation rate, male, female I
Fiscal and Monetary Policy
Govt. expenditure, percent GDP I EcGov
Govt. revenue, excluding grants, percent GDP I EcGov
Growth in the broad money supply I EcGov
Inflation rate I MCA
Overall govt. budget balance, including grants, percent GDP I MCA, EcGov
Composition of govt. expenditure II
Composition of govt. revenue II
Composition of money supply growth II

A - 4 A PPENDIX A
Business Environment
Indicator Level MDG, MCA, or EcGov a
Control of Corruption Index (-2.5 for poor to 2.5 for excellent) I EcGov
Ease of doing business ranking I EcGov
Rule of law index (-2.5 for poor to 2.5 for excellent) I MCA, EcGov
Regulatory quality index (-2.5 for poor to 2.5 for excellent) I MCA, EcGov
Government effectiveness index (-2.5 for poor to 2.5 for excellent) I MCA, EcGov
Cost of starting a business II MCA, EcGov
Procedures to enforce a contract II EcGov
Procedures to register property II EcGov
Procedures to start a business II EcGov
Time to enforce a contract II EcGov
Time to register property II EcGov
Time to start a business II MCA, EcGov
Total tax payable by business II EcGov
Business costs of crime, violence, terrorism index (1 for poor to 7 for
excellent)
Senior manager time spent dealing with government regulations II EcGov
Financial Sector
Domestic credit to private sector, percent GDP I
Interest rate spread I
Money supply, percent GDP I
Stock market capitalization rate, percent of GDP I
Credit information index (0 for poor to 6 for excellent) I
Legal rights of borrowers and lenders index (0 for poor to 10 for excellent) II
Real Interest rate II
Number of Active Microfinance Borrowers II
External Sector
Aid , percent GNI I
Current account balance, percent GDP I
Debt service ratio, percent exports I MDG
Export growth of goods and services I
Foreign direct investment, percent GDP I
Gross international reserves, months of imports I EcGov
Gross Private capital inflows, percent GDP I
Present value of debt, percent GNI I
Remittance receipts, percent exports I
Trade, percent GDP I
Trade in services, percent GDP I
Concentration of exports II
Inward FDI potential index II
Net barter terms of trade II
Real effective exchange rate (REER) II EcGov
II

CAS M ETHODOLOGY A - 5
Indicator Level MDG, MCA, or EcGov a
Structure of merchandise exports II
Trade policy index (0 for poor to 100 for excellent) II MCA, EcGov
Ease of trading across boarders ranking II EcGov
Economic Infrastructure
Internet users per 100 people I MDG
Logistics performance index, infrastructure I
Telephone density, fixed line and mobile I MDG
Overall infrastructure quality index (1 for poor to 7 for excellent) I EcGov
Quality of infrastructure—railroads, ports, air transport, and electricity II
Roads paved, percent total roads II
Science and Technology
FDI and technology transfer index (1 for poor to 7 for excellent) I
Availability of scientists and engineers index (1 for poor to 7 for excellent) I
Science & technology journal articles per million people I
IPR protection index (1 for poor to 7 for excellent) I
Health
HIV prevalence I
Life expectancy at birth I
Maternal mortality rate I MDG
Access to improved sanitation II MDG
Access to improved water source II MDG
Births attended by skilled health personnel II MDG
Child immunization rate II MCA
Prevalence of child malnutrition (weight for age) II
Public health expenditure, percent GDP II MCA, EcGov
Education
Net primary enrollment rate, male, female, total I MDG
Primary completion rate, total I
Youth literacy rate, male, female, total I
Net secondary enrollment rate I
Gross tertiary enrollment rate I
Education expenditure, primary, percent GDP II MCA, EcGov
Expenditure per student, percent GDP per capita—primary, secondary, and
tertiary
Pupil-teacher ratio, primary school II
Employment and Workforce
Labor force participation rate, total I
Rigidity of employment index (0 for minimum rigidity to 100 for
maximum)
Size and growth of the labor force I
Unemployment rate I
Economically active children, percent children ages 7-14 I
II EcGov
I EcGov

A - 6 A PPENDIX A
Indicator Level MDG, MCA, or EcGov a
Firing costs, weeks of wages II EcGov
Agriculture
Agriculture value added per worker I
Cereal yield I
Growth in agricultural value-added I
Fertilizer consumption (100 grams per hectare of arable land) II
Agricultural policy costs index (1 for poor to 7 for excellent) II EcGov
Crop production index II
Livestock production index II
a Level I = primary performance indicators, Level II = supporting diagnostic indicators
b MDG—Millennium Development Goal indicator
MCA—Millennium Challenge Account indicator
EcGov—Major indicators of economic governance, which is defined in USAID’s Strategic Management Interim Guidance to
include “microeconomic and macroeconomic policy and institutional frameworks and operations for economic stability, efficiency,
and growth.” The term therefore encompasses indicators of fiscal and monetary management, trade and exchange rate policy,
legal and regulatory systems affecting the business environment, infrastructure quality, and budget allocations.

Appendix B. Data Supplement
This supplement presents a full tabulation of the data and international benchmarks examined for
this report, along with technical notes on the data sources and definitions.

Statistical Capacity
Indicator, 0 (Doesn't
meet criteria) - 100
(Meets all criteria)
Per capita GDP
(PPP), U.S. Dollars
(PPP)
Per capita GDP,
Current U.S. Dollars
Real GDP Growth,
Percent change
Growth of Labor
Productivity, Percent
change
B-1
Investment
Productivity,
Incremental Capital-
Output Ratio (ICOR),
Ratio, Capital
investment : GDP
growth
Gross Fixed
Investment, Percent
GDP
Gross Fixed Private
Investment, Percent
GDP
Indicator Number 11P0 11P1 11P2 11P3 11S1 11S2 11S3 11S4
Sri Lanka Data
Latest Year (T) 2008 2008 2008 2008 2007 2008 2008 2008
Value Year T 70 4,581 1,972 6.0 4.5 3.8 25.3 19.3
Value Year T-1 73 4,265 1,623 6.8 5.2 3.6 24.7 20.0
Value Year T-2 69 3,920 1,430 7.7 5.7 3.8 24.9 21.3
Value Year T-3 71 3,555 1,244 6.2 3.6 5.4 23.4 19.5
Value Year T-4 72 3,263 1,063 5.4 3.6 5.7 22.6 20.2
Average Value, 5 year 71.0 3,917 1,466 6.4 4.5 4.5 24.2 20.1
Growth Trend -0.3 8.6 15.0 2.6 8.0 -12.2 2.8 -0.7
Benchmark Data
Growth Performance
Regression Benchmark 52.4 4.1 25.7 23.6
Lower Bound 46.0 2.3 21.7 21.3
Upper Bound 58.8 5.8 29.8 26.0
Latest Year Philippines 2008 2008 2008 2008 2007 2007 2007 2001
Philippines Value Latest Year 88 3,546 1,866 4.6 3.2 2.6 14.8 19.4
Latest Year Thailand 2008 2008 2008 2008 2007 2007 2007
Thailand Value Latest Year 82 8,225 4,115 2.6 4.1 4.8 26.8
LMI-Asia 70.7 6.4 4.9 25.0
LMI 68.3 3,373 1,197 5.8 4.7 24.3
High Five Avg. 91.1 50,231 47,058 14.3 123.3 51.4
Low Five Avg. 24.6 472 160 0.3 -72.1 9.5

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Human Poverty
Index, 0 (no
deprivation) - 100
(high deprivation)
Income Share,
Poorest 20%,
Percent
Poverty and Inequality
Population Living on
Less Than $1.25 PPP
per Day, Percent
Poverty Headcount,
National Poverty
Line, Percent PRSP Status, N/A
B-2
Population Below
Minimum Dietary
Energy
Consumption,
Percent
12P1 12P2 12P3 12P4 12P5 12S1
2006 2003/2004 2002 2006/07 2002 2006/07
16.9
17.8
3.6 14.0 15.2 yes 50.7
17.7 22.7
7.3 3.3 6.9 42.9 10.8
1.6 2.6 2.5 37.0 4.9
13.0 4.0 11.4 48.8 16.8
2006 2006 2006 N/A 2004
12.5 5.6 22.6 16.0
2006 2004 2004 N/A 2004
9.0 6.1 2.0 17.0
17.7
17.0 6.1 13.4
56.6 10.0 46.5 55.1 67.0
2.5 2.7 2.0 15.2 2.5

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Labor Force
Structure
(Employment in
agriculture), Percent
Labor Force
Structure
(Employment in
industry), Percent
Economic Structure
Labor Force
Structure
(Employment in
services), Percent
Output structure
(Agriculture, value
added), Percent GDP
Output structure
(Industry, value
added), Percent GDP
B-3
Output structure
(Services, etc., value
added), Percent GDP
13P1a 13P1b 13P1c 13P2a 13P2b 13P2c
2008 2008 2008 2008 2008 2008
31.3 26.6 42.1 13.4 29.4 57.3
32.3 26.2 41.2 11.7 29.9 58.4
33.5 22.8 36.8 11.3 30.6 58.0
34.3 23.4 38.7 11.8 30.2 58.0
34.5 20.8 37.9 12.5 28.6 58.8
33.2 24.0 39.3 12.1 29.7 58.1
-2.5 6.0 2.7 1.3 0.5 -0.4
11.0 22.7 63.9 7.0 28.2 58.1
4.6 20.4 58.0 2.5 23.2 52.3
17.4 25.0 69.8 11.4 33.2 63.8
2005 2005 2005 2007 2007 2007
37.0 14.9 48.1 14.1 31.7 54.2
2005 2005 2005 2007 2007 2007
42.6 20.2 37.1 11.4 43.9 44.7
18.4 39.3 45.1
14.1 30.8 52.3
67.9 38.9 80.4 56.9 70.1 85.4
0.2 9.1 24.2 0.3 9.3 18.0

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Adult Literacy Rate,
Percent
Youth Dependency
Rate, Ratio Youth :
Working Age
Population
Elderly Dependency
Rate, Ratio Elderly :
Working Age
Population
Demography and Environment
Environmental
Performance Index,
0 (Very poor
performance) - 100
(Very good
performance)
Population Size,
Million
B-4
Population Growth,
Annual percent
change
Population Living in
Urban Areas,
Percent
Resource Depletion,
Percent GNI
14P1 14P2a 14P2b 14P3 14P4a 14P4b 14P5 14P6
2006 2007 2007 2008 2008 2008 2007 2007
90.8 33.4 9.6 79.5 20.2 1.0 15.1 0.6
90.7 34.1 9.4 20.0 0.6 15.1 0.3
92.5 34.9 9.4 64.6 19.9 1.1 15.1 0.3
35.8 9.4 19.7 1.1 15.2 0.4
36.8 9.4 19.5 1.1 15.3 0.4
35.0 9.4 19.9 1.0 15.2 0.4
-2.4 0.4 0.9 -8.0 -0.4 7.8
91.4 48.4 10.5 0.2 1.0 68.7 10.4
80.2 43.7 9.3 0.0 0.6 61.3 6.1
102.6 53.2 11.8 0.3 1.3 76.2 14.6
2007 2007 2007 2008 2007 2007 2007 2007
93.4 58.5 6.6 77.9 87.9 1.9 64.2 2.1
2007 2007 2007 2008 2007 2007 2007 2007
94.1 30.0 11.5 79.2 63.8 0.6 33.0 4.3
93.4 52.1 6.6 60.4 19.9 1.7 32.6 4.4
93.3 59.2 7.4 64.8 6.9 1.7 50.0 4.0
99.8 97.7 28.7 89.1 626.4 5.0 100.0 65.9
36.2 19.9 2.8 37.4 0.0 -0.9 12.4

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Primary Completion
Rate, Male, Percent
Primary Completion
Rate, Female,
Percent
Gross Enrollment
Ratio, All Levels of
Education, Male,
Percent
Gross Enrollment
Ratio, All Levels of
Education, Female,
Percent
Gender
Life Expectancy,
Male, Years
B-5
Life Expectancy,
Female, Years
Labor Force
Participation Rate,
Male, Percent
Labor Force
Participation Rate,
Female, Percent
15P1a 15P1b 15P2a 15P2b 15P3a 15P3b 15P4a 15P4b
2006 2006 2006 2006 2006 2006 2007 2007
105.6 106.8 67.5 69.9 68.2 75.8 75.2 42.8
107.3 107.8 69.2 71.9 67.9 75.6 74.3 42.6
71.7 77.0 75.2 40.8
65.5 67.5 75.8 41.6
66.3 68.1 76.5 40.8
75.4 41.7
-0.5 1.2
77.3 81.8 70.0 76.1 87.3 55.7
72.0 75.2 66.9 73.1 84.3 47.9
82.5 88.3 73.0 79.1 90.2 63.5
2006 2006 2006 2006 2006 2006 2007 2007
90.3 97.5 77.8 81.6 69.1 73.5 80.4 49.8
2007 2007 2006 2006 2006 2006 2007 2007
98.7 103.6 76.6 79.6 65.6 74.7 80.5 65.7
94.6 99.3 67.4 65.7 64.1 67.5 80.7 52.7
91.8 92.9 68.9 71.4 65.5 72.0 77.8 49.4
103.0 109.9 78.8 84.8 91.3 85.9
31.6 22.3 39.3 40.0 56.7 17.8

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Government
Expenditure,
Percent GDP
Government
Revenue,
excluding grants,
Percent GDP
Money Supply
Growth, Percent
change
Inflation Rate,
Annual Percent
Overall Budget
Balance, Including
Grants, Percent GDP
Composition of
Government
Expenditure (Wages
and salaries),
Percent
B-6
Composition of
Government
Expenditure (Goods
and services),
Percent
Composition of
Government
Expenditure (Interest
payments), Percent
Composition of
Government
Expenditure
(Subsidies and other
current transfers),
Percent
Composition of
Government
Expenditure (Capital
expense), Percent
Composition of
Government
Expenditure (Other
expense), Percent
21P1 21P2 21P3 21P4 21P5 21S1a 21S1b 21S1c 21S1d 21S1e 21S1f
2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008
22.6 14.9 8.4 22.6 -7.7 17.7 7.8 15.1 11.6 47.7 0.1
23.5 15.8 16.5 15.8 -6.5 18.9 5.5 15.3 11.8 48.4 0.1
24.3 16.2 17.9 10.0 -6.9 17.8 6.4 14.5 13.3 48.0 0.0
15.5 19.0 11.0 -7.0 17.4 5.8 14.5 14.9 47.3 0.2
14.9 19.6 9.0 -7.3 15.9 6.5 17.5 17.5 44.5 0.3
15.5 16.3 13.7 -7.1 17.5 6.4 15.4 13.4 47.2 0.1
0.2 -18.4 22.1 -0.3 2.9 3.1 -2.4 -7.7 1.6 -33.6
32.2 14.4 5.4 -2.1
28.3 6.4 3.1 -5.1
36.0 22.4 7.7 0.9
2007 2007 2008 2008
15.8 5.4 9.3 -0.9
2007 2007 2008 2008
19.6 2.5 5.5 0.8
18.5 7.0
17.8 8.3
46.1 4,490.3 26.2 8.1
8.6 -1.1 1.4 -8.2
* global high excluding Zimbabwe
Fiscal and Monetary Policy

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Composition of
Government
Revenue (Taxes on
income, profits and
capital gains),
Percent
Composition of
Government
Revenue (Taxes on
goods and
services), Percent
Composition of
Government
Revenue (Taxes
on international
trade), Percent
Composition of
Government
Revenue (Social
contributions),
Percent
Fiscal and Monetary Policy (cont'd)
Composition of
Government
Revenue (Other
taxes), Percent
Composition of
Government
Revenue (Grants
and other
revenue),
Percent
B-7
Composition of
Money Supply
Growth (Domestic
credit to the public
sector), Percent
Composition of
Money Supply
Growth (Domestic
credit to the private
sector), Percent
Composition of
Money Supply
Growth (Domestic
credit to nonfinancial
public
enterprises),
Percent
Composition of
Money Supply
Growth (Net foreign
assets, reserves),
Percent
Composition of
Money Supply
Growth (Other items
net), Percent
21S2a 21S2b 21S2c 21S2d 21S2e 21S2f 21S3a 21S3b 21S3c 21S3d 21S3e
2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008
19.3 46.8 15.0 0.0 8.3 10.6 157.3 72.9 4.5 -110.0 -24.7
18.0 48.1 14.2 1.5 5.2 13.0 8.2 96.1 9.0 28.5 -41.7
15.9 51.1 14.6 1.3 2.9 14.2 59.5 104.8 8.1 -16.5 -55.9
12.7 55.3 13.7 1.2 17.1 18.1 101.9 -19.2 19.7 -20.5
12.9 59.8 15.2 1.1 0.0 11.0 32.2 80.4 3.4 2.2 -18.2
15.8 52.2 14.5 1.0 13.2 55.0 91.2 1.1 -15.2 -32.2
11.5 -6.3 0.1 -3.5 23.8 -2.5 -13.2
11.0 39.0 7.4 11.2 3.5 23.4
5.3 31.0 0.9 6.4 1.6 16.7
16.8 47.0 13.8 16.0 5.3 30.1
2007 2007 2007 2005 2007 2007 2007 2007 2007 2007
40.8 28.3 20.0 5.9 10.9 2.5 94.5 -35.4 201.3 -162.9
2007 2007 2007 2007 2007 2007 2008 2008 2008 2008 2008
37.1 39.8 5.5 4.8 0.5 12.4 8.7 75.6 -2.8 65.0 -46.5
54.0 64.4 40.9 46.9 18.8 78.3
1.9 4.8 -1.6 0.4 0.0 3.9

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Control of
Corruption Index, -
2.5 (Very poor
performance) to +2.5
(Excellent
performance)
Ease of Doing
Business Index,
Index Rank (1 - 181)
Rule of Law Index, -
2.5 (Very poor
performance) to +2.5
(Excellent
performance)
Regulatory Quality
Index, -2.5 (Very
poor performance) to
+2.5 (Excellent
performance)
Business Environment
Government
Effectiveness Index, -
2.5 (Very poor
performance) to +2.5
(Excellent
performance)
B-8
Cost of Starting a
Business % GNI per
Capita, Percent GNI
per Capita
Procedures to
Enforce a Contract,
Procedures
Procedures to
Register Property,
Procedures
Procedures to Start a
Business,
Procedures
Time to Enforce a
Contract, Days
22P1 22P2 22P3 22P4 22P5 22S1 22S2 22S3 22S4 22S5
2008 2009 2008 2008 2008 2009 2009 2009 2009 2009
-0.15 102 -0.01 -0.28 -0.29 7.1 40 8 4 1,318
-0.10 103 0.04 -0.11 -0.23 8.5 40 8 5 1,318
-0.13 0.07 -0.10 -0.27 9.2 40 8 8 1,318
-0.27 0.03 -0.21 -0.37 10.4 40 8 8 1,318
-0.13 -0.01 0.02 -0.37 10.7 40 8 8 1,318
-0.16 0.03 -0.14 -0.31 9.2 40 8 7 1,318
7.04 -10.22 9.57 -10.2 0.0 0.0 -18.6 0.0
-0.05 85.7 0.11 9.20 -0.03 49.1 40.0 6.6 8.5 652.4
-0.26 65.2 -0.13 9.15 -0.27 14.7 36.8 5.4 7.0 496.8
0.15 106.1 0.36 9.24 0.21 83.6 43.2 7.7 10.1 808.0
2008 2009 2008 2008 2008 2009 2009 2009 2009 2009
-0.75 140 -0.49 -0.05 0.00 29.8 37 8 15 842
2008 2009 2008 2008 2008 2009 2009 2009 2009 2009
-0.38 13 -0.03 0.26 0.11 4.9 35 2 8 479
-0.57 92 -0.43 -0.29 -0.26 16.0 40.0 6.0 8.7 591.0
-0.65 118 -0.69 -0.44 -0.58 38.5 39.5 6.0 10.0 591.0
2.39 1.96 1.88 2.20 453.5 53.6 13.6 18.5 1,611.6
-1.64 -2.01 -2.30 -1.91 0.4 22.8 1.6 2.3 184.6

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Time to Register
Property, Days
Business Environment (cont'd)
Time to Start a
Business, Days
Total Tax Payable by
Business, Percent
operating profit
Business Costs of
Crime and Violence,
1 (Significant costs) -
7 (No significant
costs)
Senior Manager Time
Spent Dealing with
Government
Regulations, Percent
22S6 22S7 22S8 22S9 22S10
2009 2009 2009 2008 2004
83 38 63.7 4.2 3.5
83 39 63.7 4.2
83 50 61.9 3.8
83 50 58.8
83 50
83 45
0.0 -8.0
51.4 36.6 38.3 3.3 11.4
8.6 13.4 26.2 2.8 9.1
94.2 59.7 50.4 3.8 13.7
2009 2009 2009 2008 2003
33 52 50.8 4.3 6.9
2009 2009 2009 2008 2006
2 33 37.8 5.2 0.4
50.0 42.3 37.7 4.2
46.0 38.0 39.5 4.2 7.9
427.5 286.7 250.0 6.6 20.0
2.3 4.3 11.5 2.1 2.5
B-9

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Domestic Credit to
Private Sector,
Percent GDP
Interest Rate Spread,
Percent
Money Supply (M2),
Percent GDP
Financial Sector
Stock Market
Capitalization Rate,
Percent GDP
Credit Information
Index, 0 (Poor) - 6
(Excellent)
B-10
Legal Rights of
Borrowers and
Lenders, 0 (Very
poor performance) -
10 (Excellent)
Real Interest Rate,
Percent
Number of
Microfinance
Borrowers,
Borrowers
23P1 23P2 23P3 23P4 23P5 23S1 23S2 23S3
2008 2008 2008 2007 2009 2009 2007 2007
28.9 8.0 34.6 23.4 5 4 2.7 711,165
33.3 8.0 36.5 27.5 3 3 1.4 774,800
34.0 6.0 37.9 23.4 4 3 0.3 682,879
32.9 5.1 38.4 17.7 4 3 0.6 376,619.0
30.6 4.4 37.7 14.4 4 3 4.9
31.9 6.3 37.0 21.3 4 3 2.0
-1.0 16.5 -2.2 14.1 2 6 -3.8
39.4 7.8 59.7 8.9 6.3 5.4 8.2
28.4 5.8 46.5 -18.3 4.4 4.1 4.3
50.4 9.9 72.8 36.1 8.2 6.8 12.2
2007 2008 2007 2007 2009 2009 2007 2007
28.8 4.3 52.9 71.7 3 3 5.7 #REF!
2007 2008 2007 2007 2009 2009 2007 2007
92.4 4.6 99.7 79.9 5 4 3.7 4,740
30.5 6.5 45.4 44.0 3.0 4.0 2.4
29.6 7.5 39.5 19.0 3.0 4.0 4.5 1,854,595.0
196.0 52.6 200.2 219.4 6.0 9.8 35.4
3.0 1.6 8.4 0.5 0.6 -20.7

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
External Aid, Percent
GNI
Current Account
Balance, Percent
GDP
Debt Service ratio,
Percent Exports
Exports Growth,
Goods and Services,
Percent change
Foreign Direct
Investment, Percent
GDP
B-11
External Sector
Gross International
Reserves, Months of
Imports
Gross Private
Capital Inflows,
Percent GDP
Present Value of Debt,
Percent GNI
Remittance Receipts,
Percent Exports
Total Trade, Percent
GDP
Trade in Services,
Percent GDP
24P1 24P2 24P3 24P4 24P5 24P6 24P7 24P8 24P9 24P10 24P11
2007 2008 2007 2008 2007 2008 2008 2007 2008 2008 2007
1.8 -9.4 7.2 7.7 1.9 1.6 11.2 41.6 28.8 64.7 13.3
2.8 -4.2 8.2 10.7 1.7 3.2 13.3 26.6 69.4 14.2
4.9 -5.3 3.7 7.9 1.1 2.9 23.5 25.4 72.3 14.9
2.5 -2.7 7.4 8.3 1.1 3.1 12.5 24.6 74.5 16.6
3.6 -3.1 7.4 11.3 1.2 2.8 11.3 21.4 80.3 16.4
3.1 -4.9 6.8 9.2 1.4 2.7 14.3 25.4 72.2 15.1
-12.2 -26.6 0.4 -5.2 12.7 -10.9 0.4 6.7 -5.0 -5.7
1.3 -11.6 14.0 5.9 10.0 2.5 8.1 85.1 2.3 119.6 41.3
-3.7 -16.9 9.0 -3.4 7.3 1.1 5.7 63.3 -8.5 102.5 35.3
6.3 -6.3 19.1 15.2 12.6 4.0 10.6 106.9 13.1 136.6 47.4
2007 2008 2007 2007 2007 2007 2005 2007 2007 2007 2007
0.4 1.0 8.8 5.6 2.0 5.7 8.4 50.9 28.1 84.8 11.0
2007 2008 2007 2007 2007 2007 2005 2007 2007 2007 2007
-0.1 -0.1 1.3 7.1 3.9 6.0 4.9 29.1 0.9 139.0 28.0
3.2 0.2 7.5 6.5 2.5 4.3 2.4 41.6 5.6 78.1 16.0
3.2 -3.1 6.3 7.2 3.7 3.5 4.0 35.0 19.9 90.8 17.6
47.0 29.8 38.2 87.7 16.8 197.8 370.8 110.7 310.4 125.3
0.0 -27.4 0.7 -2.4 0.3 -4.2 5.2 0.1 30.1 4.9

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Concentration of
Exports, Percent
Inward FDI Potential
Index, 0 (Very poor
performance) to 1
(Excellent
performance)
Net Barter Terms of
Trade, Index: 2000 =
100
Real Effective
Exchange Rate
(REER), Index: 2000
= 100
External Sector (Cont'd)
Structure of
Merchandise
Exports
(Agricultural raw
materials exports),
Percent
B-12
Structure of
Merchandise
Exports (Fuel
exports), Percent
Structure of
Merchandise
Exports
(Manufactures
exports), Percent
Structure of
Merchandise
Exports (Ores and
metals exports),
Percent
Structure of
Merchandise
Exports (Food
exports), Percent
Trade Policy Index,
0 (Very poor) - 100
(Excellent)
Ease of Trading
Across Borders
Ranking, Index
Rank (1 - 181)
24S1 24S2 24S3 24S4 24S5a 24S5b 24S5c 24S5d 24S5e 24S6 24S7
2006 2006 2007 2008 2008 2008 2008 2008 2008 2009 2009
13.3 0.1 75.8 118.1 21.7 3.1 75.7 1.5 5.6 71.0 66
16.0 0.1 79.4 100.2 18.7 2.2 78.1 1.7 6.7 69.6 60
16.2 0.1 81.8 100.0 17.7 2.7 78.5 1.7 5.3 71.6
16.3 0.1 87.3 97.7 17.2 2.1 78.0 2.3 5.0 71
17.4 0.1 92.9 90.6 17.5 1.7 78.3 2.1 3.0 77
15.8 0.1 83.5 101.3 18.6 2.4 77.7 1.8 5.1 72.0
-5.6 -6.4 -5.0 5.6 5.1 12.5 -0.7 -9.4 15.3 -1.8
70.0 0.2 110.6 1.4 18.7 17.9 0.3 36.5 73.2 89.5
60.0 0.2 96.4 1.4 13.6 5.7 -5.5 22.6 68.2 66.4
80.0 0.2 124.9 1.4 23.8 30.2 6.0 50.4 78.3 112.7
2006 2006 2007 2007 2007 2007 2007 2007 2007 2009 2009
28.0 0.2 81.7 112.3 0.5 2.4 51.0 5.1 5.9 78.6 58
2006 2006 2007 2007 2007 2007 2007 2007 2009 2009
12.2 0.2 96.1 4.7 4.5 75.8 1.8 11.5 75.6 10
31.8 0.2 95.2 1.8 2.4 74.2 2.2 11.4 70.7 78
48.6 0.2 96.8 100.8 1.7 6.5 44.4 2.4 16.5 70.3 111.8
97.5 0.5 120.7 144.6 44.3 94.9 55.1 95.0 90.3
7.3 0.1 70.2 59.1 0.0 0.9 0.0 0.4 13.8

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Internet Users, Users
per 100 people
Logistics
Performance Index -
Infrastructure, 1
(Poor) - 5 (Excellent)
Telephone Density,
Fixed Line and
Mobile, Telephones
per 100 people
Overall Infrastructure
Quality, 1 (Poor) - 7
(Excellent)
Economic Infrastructure
Quality of
Infrastructure - Air
Transport
Infrastructure Index,
1 (Poor) - 7
(Excellent)
B-13
Quality of
Infrastructure - Port
Infrastructure Quality
Index, 1 (Poor) - 7
(Excellent)
Quality of
Infrastructure - Rail
Development Index,
1 (Poor) - 7
(Excellent)
Quality of
Infrastructure -
Electricity Supply
Index, 1 (Poor) - 7
(Excellent)
Roads, Paved,
Percent
25P1 25P2 25P3 25P4 25S1a 25S1b 25S1c 25S1d 25S2
2008 2007 2008 2008 2008 2008 2008 2008 2003
5.7 2.1 72.4 3.8 4.8 4.5 3.2 4.6 81.0
3.9 53.6 3.3 4.5 4.1 2.8 4.1 85.8
2.5 36.7 2.9 3.9 3.5 2.4 3.8
1.8 23.4
1.4 16.5
3.1 40.4
35.8 37.7
25.9 2.2 92.1 3.7 3.3 0.8 4.5 25.2
20.2 2.0 77.4 3.2 2.8 0.5 4.0 10.2
31.6 2.4 106.8 4.2 3.8 1.2 5.0 40.3
2008 2007 2008 2008 2008 2008 2008 2008 2003
6.0 2.3 79.9 2.9 4.1 3.2 1.8 4.2 9.9
2008 2007 2008 2008 2008 2008 2008 2008 2000
20.0 3.2 89.6 4.8 5.8 4.4 3.1 5.5 98.5
4.6 2.2 25.5 3.0 4.2 3.4 2.8 3.8
8.6 2.2 44.2 3.0 4.1 3.3 1.9 3.9 59.5
82.6 4.2 176.6 6.6 6.7 6.6 6.5 6.8 100.0
0.2 1.5 3.4 1.8 2.5 1.6 1.1 1.6 9.4

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
FDI Technology
Transfer Index, 1
(Poor) - 7 (Excellent)
Science and Technology
Availability of
Scientists and
Engineers, 1 (Non
existent) - 7 (Widely
available)
Scientific and
Technology Journal
Articles, Articles per
Million people
IPR Protection, 1
(Poorly enforced) - 7
(Among the best)
26P1 26P2 26P3 26P4
2008 2008 2005 2008
5.1 4.9 136.0 3.7
5.1 4.7 119.0 3.8
5.0 4.5 141.0
103.0
76.0
115.0
13.1
3.3
4.1 3.2 3.5 3.2
3.8 2.8 -1,242.1 2.9
4.3 3.5 1,249.2 3.5
2008 2008 2005 2008
5.1 3.8 178.0 3.1
2008 2008 2005 2008
5.1 4.4 1,249.0 3.8
5.1 4.3 421.7 3.3
4.6 4.3 318.0 3.1
6.1 5.9 75,711.9 6.2
3.6 2.7 55.1 2.0
B-14

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
HIV Prevalence,
Percent
Life Expectancy at
Birth, Years
Maternal Mortality
Rate, Deaths per
100,000 live births
Access to Improved
Sanitation, Percent
Health
Access to Improved
Water Source,
Percent
B-15
Births Attended by
Skilled Health
Personnel, Percent
Child Immunization
Rate, Percent
Prevalence of Child
Malnutrition, Weight
for Age, Percent
Public Health
Expenditure, Percent
GDP
31P1 31P2 31P3 31S1 31S2 31S3 31S4 31S5 31S6
2007 2007 2005 2006 2006 2007 2007 2006/07 2008

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Net Primary
Enrollment Rate,
Total, Percent
Net Primary
Enrollment Rate,
Female, Percent
Net Primary
Enrollment Rate,
Male, Percent
Primary Completion
Rate, Total, Percent
Education
Youth Literacy
Rate, Total,
Percent
B-16
Youth Literacy
Rate, Male,
Percent
Youth Literacy
Rate, Female,
Percent
Net Secondary
Enrollment Rate,
Total, Percent
Gross Tertiary
Enrollment Rate,
Total, Percent
Expenditure on
Primary Education,
Percent GDP
32P1a 32P1b 32P1c 32P2 32P3a 32P3b 32P3c 32P4 32P5 32S1
2006/07 2003 2003 2006/07 2006 2006 2006 2006
97.5 99.9 99.4 88.2 97.5 97.0 97.9 0.7
0.8
96.7 99.3 98.7 0.6
99.7 0.6
0.6
0.7
5.1
93.2 94.0 94.2 100.3 97.9 102.2 74.4 25.8 0.02
86.8 87.3 88.2 90.9 92.8 90.4 66.1 19.0 0.01
99.6 100.8 100.3 109.6 103.0 113.9 82.6 32.6 0.03
2006 2006 2006 2006 2007 2007 2007 2006 2006 2006
91.4 92.5 90.5 93.8 94.4 93.6 95.3 60.4 28.5 1.5
2007 2007 2007 2007 2007 2007 2007 2007 2007 2006
93.9 93.8 94.0 101.1 98.2 98.3 98.1 76.1 49.5 1.3
83.9 84.7 83.2 97.0 95.4 93.7 97.3 60.5 19.2 1.6
88.7 86.7 89.6 95.3 97.3 97.0 97.9 1.6
99.4 99.2 99.4 99.9 99.9 99.9 97.1 79.6 6.5
41.4 36.0 46.7 48.0 56.3 39.5 7.7 0.6 0.2

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Educational
Expenditure per
Student, Primary,
Percent, GDP per
capita
Education (cont'd)
Educational
Expenditure per
Student, Secondary,
Percent, GDP per
capita
Educational
Expenditure per
Student, Tertiary,
Percent, GDP per
capita
Pupil-teacher Ratio,
Primary School,
Pupils per Teacher
32S2a 32S2b 32S2c 32S3
2006
23.5
21.9
22.5
23.4
23.4
22.9
-0.6
11.5 14.3 27.1 19.5
8.3 8.2 -24.2 15.2
14.7 20.4 78.5 23.8
2005 2005 2005 2006
8.6 9.1 11.5 34.6
2004 2004 2006 2007
13.8 15.2 28.0 17.7
29.2
28.6 50.3 519.9 63.3
6.5 6.8 10.4 9.9
B-17

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Labor Force
Participation Rate,
Total, Percent
Rigidity of
Employment Index, 0
(Minimum rigidity) -
100 (Maximum
rigidity)
Employment and Workforce
Size of the Labor
Force, People
Growth of the Labor
Force, Annual
percent change
Unemployment Rate,
Percent
B-18
Economically Active
Children, (Ages 7-14),
Percent
Firing Costs, Weeks
of wages
33P1 33P2 33P3a 33P3b 33P4 33P5 33S1
2007 2009 2007 2007 2008 2009
58.6 27 8,987,016 2.2 5.2 0.7 169
58.0 27 8,795,795 2.4 6.0 169
57.6 27 8,590,707 0.5 6.5 169
58.3 27 8,549,597 1.8 7.2 169
58.3 27 8,398,900 2.2 8.5 108
58.2 27.0 8,664,403 1.8 6.7 157
0.1 0.0 1.6 2.9 -11.7 9
72.2 19.7 70,181 2.2 9.8 5.8
67.6 10.9 -1,486,296 1.6 6.8 -2.3
76.7 28.5 1,626,659 2.7 12.8 13.8
2007 2009 2007 2007 2008 2001 2009
65.1 35.0 36,929,253 3.9 7.4 13.3 91
2007 2009 2007 2007 2008 2005 2009
72.8 18.0 36,630,187 0.6 1.4 15.1 54
64.7 27.0 8,791,172 2.2 54
63.0 33.2 2,889,548 2.4 54
87.1 74.3 315,591,526 6 28.0 232
44.8 52,572 -1 1.8

Indicator Number
Sri Lanka Data
Latest Year (T)
Value Year T
Value Year T-1
Value Year T-2
Value Year T-3
Value Year T-4
Average Value, 5 year
Growth Trend
Benchmark Data
Regression Benchmark
Lower Bound
Upper Bound
Latest Year Philippines
Philippines Value Latest Year
Latest Year Thailand
Thailand Value Latest Year
LMI-Asia
LMI
High Five Avg.
Low Five Avg.
Agriculture Value
Added per Worker,
US Dollars, Constant
2000
Cereal Yield,
Kilograms per
hectare
Growth in
Agricultural Value-
Added, Percent
change
Agriculture
Fertilizer
Consumption, 100
grams per hectare of
arable land
Agricultural Policy
Costs Index, 1
(Excessively
burdensome) - 7
(Balances all
interests)
B-19
Crop Production
Index, Index: 1999-
2001 = 100
Livestock Production
Index, Index: 1999-
2001 = 100
Agricultural Export
Growth, Percent
change
34P1 34P2 34P3 34P4 34S1 34S2 34S3 34S4
2005 2007 2007 2005 2008 2005 2005 2005
705 3,822 3.3 3,071 3.9 104.3 119.9 2.7
697 3,619 6.3 2,826 3.8 97.4 114.5 21.1
703 3,467 1.8 2,723 3.4 102.1 112.0 33.7
697 3,564 0.0 3,112 99.3 109.4 2.0
727 3,283 1.7 2,724 97.6 108.3
706 3,551 2.6 2,891 100.1 112.8
-0.6 3.2 93.5 1.4 1.1 2.5
3,540.5 2,107 1.1 845.4 3.9 103.4 102.0 14.1
2,568 1,567 -2.7 194.1 3.6 96.3 96.4 -37.4
4,513 2,647 4.9 1,497 4.2 110.5 107.6 65.7
2005 2007 2007 2005 2008 2005 2005 2007
1,097 3,261 4.9 1,310 3.8 115.1 111.2 5.8
2005 2007 2007 2005 2008 2005 2005 2007
615 2,752 3.9 1,207 4.1 105.5 99.8 5.3
595 3,164 3.7 1,499 3.8 106.8 112.9 19.1
1,237 1,939 3.2 575 3.7 112.0 112.8 14.8
50,342 7,695 15.9 17,297 5.2 142.7 155.4 362,806.7
76 438 -374.7 3 2.6 70.4 85.4 -59.8

Technical Notes
The following technical notes identify the source for each indicator, provide a concise definition,
indicate the coverage of USAID countries, and comment on data quality where pertinent. For
reference purposes, a CAS code is also given for each indicator. In many cases, the descriptive
information is taken directly from the original sources, as cited.
STATISTICAL CAPACITY
Statistical Capacity Indicator
Source: World Bank, updated annually, at
http://go.worldbank.org/20WZB3DB90
Definition: Provides and evaluation of a country’s' statistical
practice, data collection activities and key indicator
availability against a set of criteria consistent with
international recommendations. The score ranges from 0 to
100 with a score of 100 indicating that the country meets all
the criteria.
Coverage: Data are available for the vast majority of USAID
countries.
CAS Code # 01P1
GROWTH PERFORMANCE
Per capita GDP, in Purchasing Power Parity Dollars
Source: World Bank International Comparison Program, at
http://go.worldbank.org/VMCB80AB40
Definition: This indicator adjusts per capita GDP measured
in current U.S. dollars for differences in purchasing power,
using an estimated exchange rate reflecting the purchasing
power of the various local currencies.
Coverage: Data are available for about 65 USAID countries.
CAS Code #11P1
Per capita GDP, in current US Dollars
Source: IMF World Economic Outlook database, updated
every 6 months, at:
http://www.imf.org/external/ns/cs.aspx?id=28
Definition: GDP per capita is gross domestic product divided
by midyear population. GDP is the sum of gross value added
by all resident producers plus any product taxes, less any
subsidies not included in the value of the products. It is
calculated without making deductions for depreciation of
fabricated assets or for depletion and degradation of natural
resources.
Coverage: Data are available for about 85 USAID countries.
CAS Code #11P2
Real GDP Growth
Source: IMF World Economic Outlook database, updated
every six months; latest country data from IMF Article IV
consultation reports:
www.imf.org/external/np/sec/aiv/index.htm
Definition: Annual percentage growth rate of GDP at
constant local currency prices
Coverage: Data are available for about 85 USAID countries.
CAS Code #11P3
Growth of Labor Force Productivity
Source: World Development Indicators. Estimated by
calculating the annual percentage change of the ratio of GDP
(constant 2000 US$) (NY.GDP.MKTP.KD) to the population
ages 15 and older who participate in the labor force, which in
turn is the product of the total population (SP.POP.TOTL)
times the product of the percentage of the population in this
age group 15 or older (SP.POP.1564.IN.ZS +
SP.POP.65UP.TO.ZS) and the labor force participation rate
(SL.TLF.CACT.ZS).
Definition: Labor productivity is defined here as the ratio of
GDP (in constant prices) to the size of the working age
population age 15 and older that participate in the labor
force.
Coverage: Data are available for about 85 USAID countries.
CAS Code # 11S1
Investment Productivity, Incremental Capital-Output
Ratio (ICOR)
Source: International benchmark data computed from World
Development Indicators most recent publication year, based
on the five-year average of the share of fixed investment
(NE.GDI.FTOT.ZS) and the five-year average GDP growth
(NY.GDP.MKTP.KD.ZG). Updated figures for the target
country are computed from IMF Article IV consultation
reports.
Definition: The ICOR shows the amount of capital
investment incurred per extra unit of output. A high value
represents low investment productivity. The ICOR is
calculated here as the ratio of the investment share of GDP to
the growth rate of GDP, using five-year averages for both the
numerator and denominator.
Coverage: Data are available for about 81 USAID countries.
CAS Code #11S2
Gross Fixed Investment, Percentage of GDP
Source: IMF Article IV consultation report for latest country
data www.imf.org/external/np/sec/aiv/index.htm;
international benchmark from the World Development
Indicators, most recent publication series NE.GDI.FTOT.ZS.
Definition: Gross fixed investment is spending on replacing
or adding to fixed assets (buildings, machinery, equipment
and similar goods).
Coverage: Data are available for about 84 USAID countries.
CAS Code # 11S3
Gross Fixed Private Investment, Percentage of GDP
Source: IMF Article IV consultation report, for latest country
data www.imf.org/external/np/sec/aiv/index.htm; World
Development Indicators, for international comparison data
(explanation below). The estimation of this indicator involves
taking the difference between gross fixed capital formation
(percent of GDP) (NE.GDI.FTOT.ZS) and government

B - 22 T ECHNICAL N OTES
capital expenditure (percent of GDP). The latter term is the
product of government capital expenditure (percent of total
expenditure) (GB.XPK.TOTL.ZS) and total government
expenditure (percent of GDP) (GB.XPD.TOTL.GD.ZS).
Definition: This indicator measures gross fixed capital
formation by nongovernment investors, including spending
for replacement or net addition to fixed assets (buildings,
machinery, equipment, and similar goods).
Coverage: Available from World Development Indicators
2004 for about 38 USAID countries. Starting in 2005, WDI
no longer reports government capital expenditure, which is
needed to compute this variable. The reason is that the World
Bank has adopted a new system for government finance
statistics, which switches from reporting budget performance
based on cash outlays and receipts, to a modified accrual
accounting system in which government capital formation is
a balance sheet entry, and only the consumption of fixed
capital (that is, a depreciation allowance) is treated as an
expense. The template will include this variable when the
required data can be obtained from IMF Article IV
consultation report or national data sources. Group and
regression benchmarks will be computed from WDI 2004
(since group averages tend to be relatively stable).
Data Quality: National statistics offices may have different
methodologies for breaking down total government
expenditure into current and capital components. In
particular, the data on “development expenditure” in many
countries include elements of current expenditure.
CAS Code #11S4
POVERTY AND INEQUALITY
Human Poverty Index
Source: UNDP, Human Development Report
http://hdrstats.undp.org/indicators/18.html for most recent
edition; updates may be found at
http://hdr.undp.org/en/statistics/data/.
Definition: The index measures deprivation in terms of not
meeting target levels for specified economic and quality-oflife
indicators. Values are based on (1) percentage of people
not expected to survive to age 40, (2) percentage of adults
who are illiterate, and (3) percentage of people who fail to
attain a “decent living standard,” which is subdivided into
three (equally weighted) separate items: (a) percentage of
people without access to safe water, (b) percentage of people
without access to health services, and (c) percentage of
underweight children. The HPI ranges in value from 0 (zero
deprivation incidence) to 100 (high deprivation incidence).
Coverage: Data are available for about 60 USAID countries.
CAS Code #12P1
Income Share, Poorest 20 Percent
Source: World Development Indicators, most recent
publication series SI.DST.FRST.20. These are World Bank
staff estimates based on primary household survey data
obtained from government statistical agencies and World
Bank country departments. Alternative source for target
countries: the country’s Poverty Reduction Strategy Paper:
http://www.imf.org/external/np/prsp/prsp.asp
Definition: Share of total income or consumption accruing to
the poorest quintile of the population.
Coverage: Data are available for about 59 USAID countries,
if one goes back to 1997; for the period since 2000, data are
available for about 35 USAID countries.
CAS Code # 12P2
Percentage of Population Living on Less than $1.25 PPP
per Day
Source: World Development Indicators, most recent
publication series SI.POV.DDAY, original data from
Development Research Group. Alternative source for target
countries: the country’s Poverty Reduction Strategy Paper:
http://www.imf.org/external/np/prsp/prsp.asp
Definition: The indicator captures the percentage of the
population living on less than $1.25 a day at 2005
international prices. As a result of revisions in PPP exchange
rates, poverty rates for individual countries cannot be
compared with poverty rates reported in WDI editions prior
to 2009.
Coverage: Data are available for about 59 USAID countries
going back to 1997; data for 2000 or later are available for
about 40 USAID countries.
Data Quality: Poverty data originate from household survey
questionnaires that can differ widely; even similar surveys
may not be strictly comparable because of difference in
quality.
CAS Code #12P3
Poverty Headcount, National Poverty Line
Source: World Development Indicators, most recent
publication series SI.POV.NAHC. Alternative source: the
country’s Poverty Reduction Strategy Paper:
http://www.imf.org/external/np/prsp/prsp.asp
Definition: The percentage of the population living below the
national poverty line. National estimates are based on
population-weighted estimates from household surveys
Coverage: Data available for only 19 countries for 2000 or
later; data are available for about 49 countries going back to
1997. For most target countries, data can be obtained from
the PRSP.
Data Quality: Measuring the percentage of people below the
“national poverty line” has the disadvantage of limiting
international comparisons because of differences in the
definition of the poverty line. Most lower-income countries,
however, determine the national poverty line by the level of
consumption required to have a minimally sufficient food
intake plus other basic necessities.
CAS Code #12P4
PRSP Status
Source: World Bank/IMF. A list of countries with a Poverty
Reduction Strategy Paper can be found at
http://www.imf.org/external/np/prsp/prsp.asp
Definition: Yes or no variable showing whether a country has
(or not) completed a PRSP (introduced by the World Bank
and IMF to ensure host-country ownership of poverty
reduction programs).
Coverage: All countries having PRSPs are so indicated.
CAS Code #12P5
Percent of Population below Minimum Dietary Energy
Consumption
Source: UN Millennium Indicators Database at
http://millenniumindicators.un.org/unsd/mdg/Data.aspx,
based on FAO estimates.
Definition: Proportion of the population in a condition of
undernourishment. The FAO defines undernourishment as
the condition of people whose dietary energy consumption is
continuously below a minimum dietary energy requirement
for maintaining a healthy life and carrying out light physical
activity.

T ECHNICAL N OTES B - 23
Coverage: Data are available for about 82 USAID countries.
CAS Code # 12S1
ECONOMIC STRUCTURE
Employment or Labor Force Structure
Source: World Development Indicators, most recent
publication series SL.AGR.EMPL.ZS for agriculture, series
SL.IND.EMPL.ZS for industry, and series
SL.SRV.EMPL.ZS for services. Alternative source: CIA
World Fact Book:
https://www.cia.gov/library/publications/the-worldfactbook/index.html
Definition: Employment in each sector is the proportion of
total employment recorded as working in that sector.
Employees are people who work for a public or private
employer and receive remuneration in wages, salary,
commission, tips, piece rates, or pay in kind. Agriculture
includes hunting, forestry, and fishing. Industry includes
mining and quarrying (including oil production),
manufacturing, electricity, gas and water, and construction.
Services include wholesale and retail trade and restaurants
and hotels; transport, storage, and communications;
financing, insurance, real estate, and business services; and
community, social, and personal services.
Coverage: Data are available for about 37 USAID countries.
For most target countries, data can be obtained from PRSP.
Data Quality: Employment figures originate with
International Labor Organization. Some countries report
labor force structure instead of employment, thus the data
must be checked carefully before comparisons are made.
CAS Code #13P1
Output Structure
Source: World Development Indicators, most recent
publication series NV.AGR.TOTL.ZS for value added in
agriculture as a percentage of GDP; series
NV.IND.TOTL.ZS for the share of industry; and
NV.SRV.TETC.ZS for the share of services.
Definition: The output structure is composed of value added
by major sector of the economy (agriculture, industry, and
services) as percentages of GDP, where value added is the
net output of a sector after all outputs are added up and
intermediate inputs are subtracted. Value added is calculated
without deductions for depreciation of fabricated assets or
depletion and degradation of natural resources. Agriculture
includes forestry, hunting, and fishing, as well as cultivation
of crops and livestock production. Industry includes
manufacturing, mining, construction, electricity, water, and
gas. Services include wholesale and retail trade (including
hotels and restaurants), transport, and government, financial,
professional, and personal services such as education, health
care, and real estate services.
Coverage: Data are available for about 86 USAID countries.
Data Quality: A major difficulty in compiling national
accounts is the extent of unreported activity in the informal
economy. In developing countries a large share of
agricultural output is either not exchanged (because it is
consumed within the household) or not exchanged for
money. This production is estimated indirectly using
estimates of inputs, yields, and area under cultivation. This
approach can differ from the true values over time and across
crops. Ideally, informal activity in industry and services is
measured through regular enterprise censuses and surveys. In
most developing countries such surveys are infrequent, so
prior survey results are extrapolated.
CAS Code #13P2
DEMOGRAPHY AND ENVIRONMENT
Adult Literacy Rate
Source: World Development Indicators, most recent
publication series SE.ADT.LITR.ZS, based on UNESCO
calculations.
Definition: Percentage of people ages 15 and older who can
read and write a short, simple statement about their daily life.
Coverage: Data are available for about 66 USAID countries.
Data Quality: In practice, literacy is difficult to measure. A
proper estimate requires census or survey measurements
under controlled conditions. Many countries estimate the
number of illiterate people from self-reported data, or by
taking people with no schooling as illiterate.
CAS Code # 14P1
Youth Dependency Rate
Source: World Development Indicators, most recent
publication series.
Definition: Youth dependency rate is calculated as the
percentage of the population below age 15 (WDI
SP.POP.0014.TO.ZS) divided by the working-age population
(those ages 15–64) (WDI SP.POP.1564.TO.ZS)
Coverage: Data are available for about 89 USAID countries.
CAS Code #14P2a
Elderly Dependency Rate
Source: World Development Indicators, most recent
publication series.
Definition: This is calculated as percentage of the population
over age 65 (WDI SP.POP.65UP.TO.ZS) divided by
working-age population (those ages 15–64) (WDI
SP.POP.1564.TO.ZS)
Coverage: Data are available for about 89 USAID countries.
CAS Code #14P2b
Environmental Performance Index
Source: Center for International Earth Science Information
Network (CIESIN) at Columbia University, and the Center
for Environmental Law and Policy at Yale University.
http://epi.yale.edu/CountryScores.
Definition: The Environmental Performance Index (EPI) is a
composite index of national environmental protection, which
tracks (1) environmental health, (2) air quality, (3) water
resources, (4) biodiversity and habitat, (5) productive natural
resources, and (6) sustainable energy. The index is a
weighted average of these six policy categories, with more
weight given environmental health, (i.e., EPI = 0.5 ×
environmental health + 0.1 × (air quality + water resources +
productive natural resources + biodiversity and habitat +
sustainable energy)). The index values range from 0 (very
poor performance) to 100 (very good performance).
Coverage: Data are available for about 80 USAID countries.
Data quality: The 2006 pilot EPI and 2008 EPI differ in
several strucutural and substantive areas. As a result
comparison berween both years are not appropriate.
CAS Code #14P3
Population Size and Growth
Source: World Development Indicators, most recent
publication series SP.POP.TOTL for total population, and
series SP.POP.GROW for the population growth rate.

B - 24 T ECHNICAL N OTES
Definition: Total population counts all residents regardless of
legal status or citizenship—except refugees not permanently
settled in the country of asylum. Annual population growth
rate is based on the de facto definition of population.
Coverage: Data are available for about 88 USAID countries.
CAS Code # 14P4
Population Living In Urban Areas
Source: World Development Indicators, most recent
publication series SP.URB.TOTL.IN.ZS.
Definition: Urban population is the share of the total
population living in areas defined as urban in each country.
The calculation considers all residents regardless of legal
status or citizenship, except refugees.
Coverage: Data are available for about 86 USAID countries.
Data Quality: The estimates are based on national definitions
of what constitutes an urban area; since these definitions vary
greatly, cross-country comparisons should be made with
caution.
CAS Code #14P5
Resource Depletion, Percent GNI
Source: World Development Indicators, most recent
publication series: NY.ADJ.DNGY.GN.ZS (energy),
NY.ADJ.DMIN.GN.ZS (minerals), NY.ADJ.DFOR.GN.ZS
(forests). Sum of energy depletion + mineral depletion + net
forest depletion, as a percentage of gross national income.
Definition: Resource depletion, as a percent of GNI is an
indicator of environmental sustainability.
Energy depletion is equal to the product of unit resource rents
and the physical quantities of energy extracted. It covers
crude oil, natural gas, and coal.
Mineral depletion is equal to the product of unit resource
rents and the physical quantities of minerals extracted. It
refers to bauxite, copper, iron, lead, nickel, phosphate, tin,
zinc, gold, and silver.
Net forest depletion is calculated as the product of unit
resource rents and the excess of roundwood harvest over
natural growth.
Coverage: Data are available for about 80 USAID countries.
Data Quality: Though each component is itself constructed
from an estimate, the methodology is reasonably sound. Note
however, the World Bank does not provide an estimate of
soil depletion.
CAS Code #14P6
GENDER
Primary Completion Rate, Male and Female
Source: World Development Indicators, most recent
publication series: SE.PRM.CMPT.MA.ZS (male),
SE.PRM.CMPT.FE.ZS (female). Based on data from United
Nations Education, Scientific, and Cultural Organization
(UNESCO) Institute of Statistics.
Definition: Primary completion rate is the percentage of
students completing the last year of primary school. It is
calculated by taking the total number of students in the last
grade of primary school, minus the number of repeaters in
that grade, divided by the total number of children of official
graduation age.
Coverage: Data are available for about 128 USAID
countries.
Data Quality: Completion rates are based on data collected
during annual school surveys, typically conducted at the
beginning of the school year. The indicator does not measure
the quality of the education.
CAS Code #15P1
Gross Enrollment Ratio, All Levels of Education, Male
and Female
Source: United Nations Organization for Education, Science,
and Culture UNESCO:
http://stats.uis.unesco.org/unesco/TableViewer/document.asp
x?ReportId=136&IF_Language=eng&BR_Topic=0
Definition: The number of students enrolled in primary,
secondary, and tertiary levels of education by gender,
regardless of age, expressed as a percentage of the population
of official school age for the three levels by gender.
Coverage: Data are available for about 80 USAID countries.
Data Quality: Enrollment ratios are based on data collected
during annual school surveys, typically conducted at the
beginning of the school year.
CAS Code #15P2
Life Expectancy, Male and Female
Source: Estimated from UNDP Human Development
Indicators:
http://hdrstats.undp.org/indicators/271.html and
http://hdrstats.undp.org/indicators/270.html for most recent
edition; updates may be found at
http://hdr.undp.org/en/statistics/data/.
Definition: The number of years a newborn male or female
infant would live if prevailing patterns of age and sexspecific
mortality rates at the time of birth were to stay the
same throughout the child’s life.
Coverage: Data are available for about 85 USAID countries.
CAS Code #15P3
Labor Force Participation Rate, Male and Female
Source: World Development Indicators, most recent
publication series: SL.TLF.CACT.MA.ZS (male)
SL.TLF.CACT.FE.ZS (female). Based on data from
International Labour Organization (ILO)
Definition: The proportion of the population ages 15 and
older that is economically active: all people who supply labor
for the production of goods and services during a specified
period. It includes both the employed and the unemployed.
Coverage: Data are available for about 88 USAID countries.
CAS Code #15P4
FISCAL AND MONETARY POLICY
In the World Development Indicators for 2005, the World
Bank adopted the Government Finance Statistics 2001
system for government budget statistics, switching from data
based on cash outlays and receipts to a system with revenues
booked on receipt and expenses booked on accrual, in
accordance with the IMF’s Government Financial Statistics
(GFS) Manual, 2001. On the revenue side, the changes are
minor, and comparisons to the old system may still be valid.
There is a major change, however, in the reporting of capital
outlays, which are now treated as balance sheet entries; only
the annual capital consumption allowance (depreciation) is
reported as an expense. Hence, the data on total expense is
not comparable to the former data on total expenditure. In
addition, WDI 2005 now provides data on the government’s
cash surplus/deficit; this differs from the previous concept of
the overall budget balance by excluding net lending minus
repayments (which are now a financing item under net

T ECHNICAL N OTES B - 25
acquisition of financial assets). Most countries do not use the
new GFS system, so country coverage of fiscal data in WDI
2005 is limited. For this reason, the template continues to use
data from IMF Article IV consultations and domestic country
websites on a cash outlays and receipts system.
Government Expenditure, Percentage of GDP
Source: IMF Article IV consultation report for latest country
data www.imf.org/external/np/sec/aiv/index.htm;
Definition: Total expenditure of the central government as a
percent of GDP.
Coverage: Data available for about 70 percent of USAID
countries.
CAS Code # 21P1
Government Revenue, excluding grants, Percentage of
GDP
Source: IMF Article IV consultation report for latest country
data http://www.imf.org/external/np/sec/aiv/index.htm ;
World Development Indicators for benchmarking data
(GC.REV.XGRT.GD.ZS). Original data from the IMF,
Government Finance Statistics Yearbook and data file, and
World Bank estimates.
Definition: Government revenue includes all revenue to the
central government from taxes and non-repayable receipts
(other than grants), measured as a share of GDP. Grants
represent monetary aid going to the central government that
has no repayment requirement.
Gaps: Data missing for about 24 USAID countries.
CAS Code # 21P2
Growth in Broad Money Supply
Source: Latest country data are from national data sources or
from IMF Article IV consultation report:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data are from World Development Indicators, most recent
publication, series FM.LBL.MQMY.ZG. Original source of
WDI data is IMF, International Financial Statistics, and
World Bank estimates.
Definition: Average annual growth rate in the broad money
supply, M2 (money plus quasi-money) measured as the
change in end-of-year totals relative to the preceding year.
M2 comprises the sum of currency outside banks, checking
account deposits other than those of the central government,
and the time, savings, and foreign currency deposits of
resident sectors other than the central government. M2
corresponds to the sum of lines 34 and 35 in the IMF’s
International Financial Statistics.
Coverage: Data are available for about 81 USAID countries.
CAS Code #21P3
Inflation Rate
Source: IMF World Economic Outlook database, updated
every six months, at
http://www.imf.org/external/ns/cs.aspx?id=28
Definition: Inflation as measured by the consumer price
index reflects the annual percentage change in the cost to the
average consumer of acquiring a basket of goods and services
that may be fixed or changed at specific intervals.
Coverage: Data are available for about 85 USAID countries.
Data Quality: For many developing countries, figures for
recent years are IMF staff estimates. Additionally, data for
some countries are for fiscal years.
CAS Code # 21P4
Overall Budget Balance, Including Grants, Percentage of
GDP
Source: For countries using the new GFS system (see
explanation at the beginning of this section), benchmarking
data on the government’s cash surplus/deficit are obtained
from World Development Indicators, most recent publication
series GC.BAL.CASH.GD.ZS. For countries that are not yet
using the new system, benchmarking data on the overall
budget balance are obtained from WDI 2004, series
GB.BAL.OVRL.GD.ZS. Latest country data are obtained
from national data sources or from IMF Article IV
consultation reports:
www.imf.org/external/np/sec/aiv/index.htm.
Definition: The cash surplus/deficit is revenue (including
grants) minus expenses, minus net acquisition of nonfinancial
assets. This is close to the previous concept of overall budget
balance, differing only in that it excludes net lending (which
is now treated as a financing item, under net acquisition of
financial assets).
For countries that are not using the new GFS system, the
template will continue to focus on the overall budget
balance, using data from the alternative sources indicated
above. The overall budget deficit is defined as the difference
between total revenue (including grants) and total
expenditure.
Both concepts measure the central government’s financing
requirement, which must be met by domestic or foreign
borrowing. As noted above, they differ in that the new cash
surplus/deficit variable excludes net lending (which is usually
a minor item).
Coverage: Data are available in WDI 2006 for less than half
USAID countries.
CAS Code # 21P5
Composition of Government Expenditure
Source: The latest country and benchmark data are taken
from national data sources or from IMF Article IV
consultation reports:
www.imf.org/external/np/sec/aiv/index.htm.
Definition: Central government expenditure, broken down
into the following six categories: (1) wages and salaries; (2)
goods and services; (3) interest payments; (4) subsidies and
other current transfers; (5) capital expenditures; and (6) other
expense.
Coverage: Data are available for the majority of USAID
countries
Data Quality: Many countries report their revenue in
noncomparable categories. Budget data are compiled by
fiscal year. If the fiscal year differs from the calendar year,
ratios to GDP may be calculated by interpolating budget data
from two adjacent fiscal years.
CAS Code # 21S1
Composition of Government Revenue
Source: The latest country and comparison country data are
taken from national data sources or from IMF Article IV
consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data are taken directly from WDI 2005 database: (1) taxes on
goods and services (% of revenue), series
GC.TAX.GSRV.RV.ZS; (2) taxes on income, profits and
capital gains (% of revenue), series GC.TAX.YPKG.RV.ZS;
(3) taxes on international trade (% of revenue), series
GC.TAX.INTT.RV.ZS; (4) other taxes (% of revenue), series
GC.TAX.OTHR.RV.ZS; (5) social security contributions (%
of revenue), series GC.REV.SOCL.ZS; and (6) grants and
other revenue (% of revenue), series GC.REV.GOTR.ZS.

B - 26 T ECHNICAL N OTES
Definition: Breakdown of central government revenue
sources by categories outlined above. Each source of revenue
is expressed as a percentage of total revenue.
Coverage: Data are available for about 46 USAID countries.
Data Quality: Many countries report their revenue in
noncomparable categories. If the fiscal year differs from the
calendar year, then the ratios to GDP may be calculated by
interpolating budget data from two adjacent fiscal years.
CAS Code # 21S2
Composition of Money Supply Growth
Source: Constructed using national data sources or IMF
Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm.
Definition: Identifies the sources of the year-to-year change
in the broad money supply (M2), disaggregated into five
categories: (1) net domestic credit to the public sector, (2) net
domestic credit to the private sector, and (3) net foreign
assets (reserves), (4) net credit to non-financial public
enterprises, and (5) other items, net. Each component is
expressed as a percentage of the annual change (December to
December) in M2.
Coverage: Data are available for about 86 USAID countries.
CAS Code # 21S3
BUSINESS ENVIRONMENT
Control of Corruption Index
Source: World Bank Institute
http://www.govindicators.org
Definition: The Control of Corruption index is an
aggregation of various indicators that measure the extent to
which public power is exercised for private gain, including
both petty and grand forms of corruption, as well as "capture"
of the state by elites and private interests. Index ranges from -
2.5 (for very poor performance) to +2.5 (for excellent
performance).
This is also an MCC indicator, under the criterion of ruling
justly. The MCC rescales the values as percentile rankings
relative to the set of MCA eligible countries, ranging from a
value from 0 (for very poor performance) to 100 (for
excellent performance). Some country reports use the MCC
scaling.
Coverage: Data are available for nearly all USAID countries.
Data Quality: This indicator uses perception and opinions
gathered from local businessmen as well as third-party
experts; thus, the indicator is largely subjective. Also
standard errors are large. For both reasons, international
comparisons are problematic, though widely used.
CAS Code # 22P1
Ease of Doing Business Index
Source: World Bank, Doing Business Indictors
http://www.doingbusiness.org/
Definition: The Ease of Doing Business index ranks
economies from 1 to 181. The index is calculated as the
ranking on the simple average of country percentile rankings
on each of the 10 topics covered in Doing Business: starting a
business, dealing with licenses, hiring and firing, registering
property, getting credit, protecting investors, paying taxes,
trading across borders, enforcing contracts, and closing a
business.
Coverage: Data are available for nearly all USAID countries.
CAS Code # 22P2
Rule of Law Index
Source: World Bank Institute, http://www.govindicators.org
This indicator is based on the perceptions of the legal system,
drawn from 12 data sources.
Definition: The Rule of Law index is an aggregation of
various indicators that measure the extent to which agents
have confidence in and abide by the rules of society. Index
ranges from -2.5 (for very poor performance) to +2.5 (for
excellent performance).
Coverage: Data are available for nearly all USAID countries.
Data Quality: This index is best used with caution for
relative comparisons between countries in a single year,
because the standard errors are large. Using the index to track
a country’s progress over time is also difficult because the
index does not compensate for changes in the world average.
For instance, if the world average decreases in a given year, a
country whose score appears to increase may not actually
have tangible improvements in its legal environment.
CAS Code #22P3
Regulatory Quality Index
Source: World Bank Institute;
http://www.govindicators.org
Definition: The regulatory quality index measures the ability
of the government to formulate and implement sound policies
and regulations that permit and promote private sector
development. It is computed from survey data from multiple
sources. The index values range from -2.5 (very poor
performance) to +2.5 (excellent performance).
This is also an MCC indicator, under the criterion of
encouraging economic freedom. The MCC rescales the
values as percentile rankings relative to the set of MCA
eligible countries, ranging from a value from 0 (for very poor
performance) to 100 (for excellent performance). Some
country reports use the MCC scaling.
Gaps: Data are available for nearly all USAID countries.
Data Quality: This index is best used with caution for
relative comparisons between countries in a single year,
because the standard errors are large. It is also difficult to use
the index to track a country’s progress over time because the
index does not compensate for changes in the world average.
For instance, if the world average decreases in a given year, a
country whose score appears to increase may not actually
have tangible improvements in their legal environment.
CAS Code #22P4
Government Effectiveness Index
Source: World Bank Institute, http://www.govindicators.org
Definition: This index, based on 17 component sources,
measures “the quality of public services, the quality of the
civil service and the degree of its independence from political
pressures, the quality of policy formulation and
implementation, and the credibility of the government’s
commitment to such policies.” The index values range from
-2.5 (very poor performance) to +2.5 (excellent
performance).
Coverage: Data are available for nearly all USAID countries.
CAS Code #22P5
Cost of Starting a Business
Source: World Bank, Doing Business; Starting a Business
category:
http://www.doingbusiness.org/ExploreTopics/StartingBusine
ss/

T ECHNICAL N OTES B - 27
Definition: Legally required cost to starting a simple limited
liability company, expressed as percentage of GNI per capita.
Coverage: Data are available for nearly all USAID countries.
CAS Code #22S1
Procedures to Enforce a Contract
Source: World Bank, Doing Business; Enforcing Contracts
category:
http://www.doingbusiness.org/ExploreTopics/EnforcingCont
racts/
Definition: The number of procedures required to enforce a
valid contract through the court system, with procedure
defined as any interactive step the company must take with
government agencies, lawyers, notaries, etc. to proceed with
enforcement action.
Coverage: Data are available for nearly all USAID countries.
CAS Code # 22S2
Procedures to Register Property
Source: World Bank, Doing Business; Registering Property
category:
http://www.doingbusiness.org/ExploreTopics/RegisteringPro
perty/
Definition: Number of procedures required to register the
transfer of title for business property. A procedure is defined
as any step involving interaction between a company or
individual and a third party that is necessary to complete the
property registration process.
Coverage: Data are available for nearly all USAID countries.
CAS Code #22S3
Procedures to Start a Business
Source: World Bank, Doing Business; Starting a Business
category:
http://www.doingbusiness.org/ExploreTopics/StartingBusine
ss/
Definition: The number of procedural steps required to
legalize a simple limited liability company. A procedure is an
interaction of a company with government agencies, lawyers,
auditors, notaries, and the like, including interactions
required to obtain necessary permits and licenses and
complete all inscriptions, verifications, and notifications to
start operations.
Coverage: Data are available for nearly all USAID countries.
CAS Code # 22S4
Time to Enforce a Contract
Source: World Bank, Doing Business; Enforcing Contracts
category:
http://www.doingbusiness.org/ExploreTopics/EnforcingCont
racts/
Definition: Minimum number of days required to enforce a
contract through the court system.
Coverage: Data are available for nearly all USAID countries.
CAS Code # 22S5
Time to Register Property
Source: World Bank, Doing Business; Registering Property
category:
http://www.doingbusiness.org/ExploreTopics/RegisteringPro
perty/
Definition: The time required to accomplish the full sequence
of procedures to transfer a property title from the seller to the
buyer when a business purchases land and a building in a
peri-urban area of the country’s most populous city. Every
required procedure is included whether it is the responsibility
of the seller, the buyer, or where it is required to be
completed by a third party on their behalf.
Coverage: Data are available for nearly all USAID countries.
CAS Code #22S6
Time to Start a Business
Source: World Bank, Doing Business; Starting a Business
category:
http://www.doingbusiness.org/ExploreTopics/StartingBusine
ss/
Definition: The number of calendar days needed to complete
the required procedures for legally operating a business. If a
procedure can be speeded up at additional cost, the fastest
procedure, independent of cost, is chosen.
Coverage: Data are available for nearly all USAID countries.
CAS Code #22S7
Total Tax Payable by Business
Source: World Bank, Doing Business, Paying Taxes
Category:
http://www.doingbusiness.org/ExploreTopics/PayingTaxes/
Definition: The amount of taxes payable by a medium-sized
business in the second year of operation, expressed as share
of commercial profits. The total amount of taxes is the sum
of all the different taxes payable after accounting for
deductions and exemptions. The taxes withheld but not paid
by the company are excluded. The taxes included can be
divided into five categories: profit or corporate income tax,
social security contributions and other labor taxes paid by the
employer, property taxes, turnover taxes and other small
taxes (such as municipal fees and vehicle and fuel taxes).
Commercial profits are defined as sales minus cost of goods
sold, minus gross salaries, minus administrative expenses,
minus other deductible expenses, minus deductible
provisions, plus capital gains (from the property sale) minus
interest expense, plus interest income and minus commercial
depreciation.
Coverage: Data are available for nearly all USAID countries
CAS Code #22S8
Business Costs of Crime, Violence and Terrorism Index
Source: Global Competitiveness Report, World Economic
Forum.
Definitions: The index measures executives’ perceptions of
the business costs of terrorism in their respective country.
Executives grade, on a scale from 1 to 7, whether crime,
violence and terrorism impose (1) significant costs on
business, or (7) do not impose significant costs on business.
Coverage: Data are available for about 52 USAID countries.
Data Quality: Comparisons between countries are difficult,
because the data are based on executive perceptions.
CAS Code #22S9
Senior Manager Time Spent Dealing with Government
Regulations
Source: World Bank Enterprise Surveys, Bureaucracy
section, www.enterprisesurveys.org
Definitions: Average percentage of senior managers’ time
that is spent in a typical week dealing with requirements
imposed by government regulations such as taxes, customs,
labor regulations, licensing and registration, and dealings
with officials, and completing forms.

B - 28 T ECHNICAL N OTES
Coverage: Data available for about 80 USAID countries.
Data Quality: Same-timeframe comparisons between
countries may be difficult; 15-20 enterprise surveys are
conducted per year, with country updates expected
approximately every three to five years. Surveys are taken of
hundreds of entrepreneurs per country who describe the
impact of their country’s investment climate on their firm.
CAS Code #22S10
FINANCIAL SECTOR
Domestic Credit to Private Sector, Percentage of GDP
Source: IMF-International Financial Statistics financial
section, where available; IMF Article IV consultation reports
or national data sources for latest country data; World
Development Indicators, most recent publication series
FS.AST.PRVT.GD.ZS for benchmarking data. The WDI data
originate with the IMF, International Financial Statistics and
data files, and World Bank estimates.
Definition: Domestic credit to private sector refers to
financial resources provided to the private sector, such as
through loans, purchases of non-equity securities, and trade
credits and other accounts receivable, that establish a claim
for repayment. For some countries, these claims include
credit to public enterprises.
Coverage: Data are available for about 82 USAID countries.
CAS Code # 23P1
Interest Rate Spread
Source: World Development Indicators, most recent
publication series FR.INR.LNDP. Original data from IMF,
International Financial Statistics and data files.
Definition: The difference between the average lending and
borrowing interest rates charged by commercial or similar
banks on domestic currency deposits.
Coverage: Data are available for about 66 USAID countries.
CAS Code # 23P2
Money Supply, Percentage of GDP
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data from World Development Indicators, most recent
publication series FM.LBL.MQMY.GD.ZS. WDI data
originate from IMF, International Financial Statistics and
data files, and World Bank and OECD GDP estimates.
Definition: Money supply (M2), also called broad money, is
defined as nonbank private sector’s holdings of notes, coins,
and demand deposits, plus savings deposits and foreign
currency deposits. Ratio of M2 to GDP is calculated to assess
the degree of monetization of an economy.
Coverage: Data are available for about 81 USAID countries.
Data Quality: In some countries M2 includes certificates of
deposits, money market instruments, and treasury bills.
CAS Code # 23P3
Stock Market Capitalization Rate, Percentage of GDP
Source: World Development Indicators, most recent
publication, series CM.MKT.LCAP.GD.ZS.
Definition: This variable is defined as the market
capitalization, also known as market value (the share price
times the number of shares outstanding), of all the domestic
shares listed on the country’s stock exchange as a percentage
of GDP.
Coverage: Data are available for about 54 USAID countries.
CAS Code # 23P4
Credit Information Index
Source: World Bank, Doing Business; Getting Credit
Category:
http://www.doingbusiness.org/ExploreTopics/GettingCredit/
Definition: The credit information index measures rules
affecting the scope, accessibility and quality of credit
information available through either public or private credit
registries. The index ranges from 0 to 6, with higher values
indicating the availability of more credit information, from
either a public registry or a private bureau, to facilitate
lending decisions.
Coverage: Data are available for nearly all USAID countries.
Data Quality: The indicator is subjective, as it is based on an
opinion poll.
CAS Code # 23P5
Legal Rights of Borrowers and Lenders Index
Source: World Bank Doing Business; Getting Credit
category:
http://www.doingbusiness.org/ExploreTopics/GettingCredit/
The index is based on data collected through research of
collateral and insolvency laws supported by survey data on
secured transactions laws.
Definition: The index measures the degree to which collateral
and bankruptcy laws facilitate lending. It ranges in value
from 0 (very poor performance) to 10 (excellent
performance). It includes three aspects related to legal rights
in bankruptcy, and seven aspects found in collateral law.
Coverage: Data are available for nearly all USAID countries.
CAS Code # 23S1
Real Interest Rate
Source: World Development Indicators, most recent
publication series FR.INR.RINR.
Definition: Real interest rate is the lending interest rate
adjusted for inflation, as measured by the GDP deflator.
Coverage: Data are available for about 68 USAID countries.
CAS Code # 23S2
Number of Active Microfinance Borrowers
Source: The Mix Market.
http://www.mixmarket.org/en/demand/demand.quick.search.
asp.
Definition: An aggregate of the number of current borrowers
from microfinance institutions as reported by microfinance
institutions to The Mix Market.
Coverage: Data are available for about 68 USAID countries.
Data Quality: Data are only available for those microfinance
institutions that report to the Mix Market and data are not
always updated in a timely fashion.
CAS Code # 23S3

T ECHNICAL N OTES B - 29
EXTERNAL SECTOR
Aid, Percentage of GNI
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data from World Development Indicators, most recent
publication series DT.ODA.ALLD.GN.ZS.
Definition: The indicator measures official development
assistance from OECD countries and official aid from non-
OECD countries, as a percentage of the recipient’s gross
national income.
Coverage: Data are available for about 84 USAID countries.
Data Quality: Data do not include aid given by recipient
countries to other recipient countries, and may not be
consistent with the country’s balance sheets, because data are
collected from donors.
CAS Code #24P1
Current Account Balance, Percentage of GDP
Source: Latest country data from national data sources or
IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data from World Development Indicators, most recent
publication series BN.CAB.XOKA.GD.ZS, based on IMF,
Balance of Payments Statistics Yearbook and data files,
World Bank staff estimates, and World Bank and OECD
GDP estimates.
Definition: Current account balance is the sum of net exports
of goods, services, net income, and net current transfers. It is
presented here as a percentage of a country’s gross domestic
product.
Coverage: Data are available for about 79 USAID countries.
CAS Code # 24P2
Debt Service ratio
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data from World Development Indicators, most recent
publication, series DT.TDS.DECT.EX.ZS, based on World
Bank, Global Development Finance data.
Definition: The debt service is the sum of interest and
principal payments made by or due from a country in a given
year, expressed as a percentage of exports of goods and
services.
Coverage: Data are available for about 77 USAID countries.
Data Quality: See data quality comments to the Present value
of debt, percent of GNI regarding quality of debt data
reported.
CAS Code # 24P3
Exports Growth, Goods and Services
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data from World Development Indicators, most recent
publication, series NE.EXP.GNFS.KD.ZG, based on World
Bank national accounts data, and OECD National Accounts
data files.
Definitions: Annual growth rate of exports of goods and
services based on constant local currency units. Exports
include the value of merchandise, freight, insurance,
transport, travel, royalties, license fees, and other services,
such as communication, construction, financial, information,
business, personal, and government services. They exclude
labor and property income (formerly called factor services),
as well as transfer payments.
Coverage: Data are available for about 81 USAID countries.
CAS Code # 24P4
Foreign Direct Investment, Percentage of GDP
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data from World Development Indicators, most recent
publication, series BX.KLT.DINV.DT.GD.ZS, based on
IMF, International Financial Statistics and Balance of
Payments databases, World Bank, Global Development
Finance, and World Bank and OECD GDP estimates.
Definition: Foreign direct investment is the net inflow of
investment to acquire a lasting management interest
(10 percent or more of voting stock) in an enterprise
operating in an economy other than that of the investor. It is
the sum of equity capital, reinvestment of earnings, other
long-term capital, and short-term capital as shown in the
balance of payments. This series shows net inflows in the
reporting economy.
Coverage: Data are available for about 82 USAID countries.
CAS Code #24P5
Gross International Reserves, Months of Imports
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data from World Development Indicators, most recent
publication, series FI.RES.TOTL.MO.
Definition: Gross international reserves comprise holdings of
monetary gold, special drawing rights (SDRs), the reserve
position of members in the IMF, and holdings of foreign
exchange under the control of monetary authorities expressed
in terms of the number of months of imports of goods and
services.
Coverage: Data are available for about 77 USAID countries.
CAS Code # 24P6
Gross Private Capital Inflows, Percentage of GDP
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm Benchmarking
data derived from the International Financial Statistics (sum
of lines 78BED and 78BGD, divided by GDP).
Definition: Gross private capital inflows are the sum of the
direct and portfolio investment inflows recorded in the
balance-of-payments financial account. The indicator is
calculated as a ratio to GDP in U.S. dollars.
Coverage: Information on coverage is not easily accessible.
Data Quality: Capital flows are converted to U.S. dollars at
the IMF’s average official exchange rate for the year shown.
CAS Code #24P7
Present Value of Debt, Percentage of GNI
Source: World Development Indicators, most recent
publication series DT.DOD.PVLX.GN.ZS, based on Global
Development Finance data.
Definition: Present value of debt is the sum of short-term
external debt plus the discounted sum of total debt service
payments due on public, publicly guaranteed, and private

B - 30 T ECHNICAL N OTES
non-guaranteed long-term external debt over the life of
existing loans. The indicator measures the value of debt
relative to the GNI.
Coverage: Data are available for about 80 USAID countries.
Data Quality: The coverage and quality of debt data vary
widely across countries because of the wide spectrum of debt
instruments, the unwillingness of governments to provide
information, and a lack of capacity in reporting.
Discrepancies are significant when exchange rate
fluctuations, debt cancellations, and rescheduling occur.
CAS Code # 24P8
Remittances Receipts, Percentage of Exports
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data are obtained from World Development Indicators, most
recent publication and remittances data compiled by the
World Bank at http://go.worldbank.org/QOWEWD6TA0.
The figure is constructed by dividing workers’ remittances
(receipts), by exports of goods and services, WDI series
BX.GSR.GNFS.CD.
Definition: Workers’ remittances are current transfers by
migrants who are employed or intend to remain employed for
more than a year in another economy in which they are
considered residents. The indicator is the ratio of remittances
to exports.
Coverage: Data are available for all USAID countries.
CAS Code # 24P9
Trade, Percentage of GDP
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data from World Development Indicators, most recent
publication, series NE.TRD.GNFS.ZS.
Definition: The sum of exports and imports of goods and
services divided by the value of GDP, all expressed in current
U.S. dollars.
Coverage: Data available for about 84 USAID countries.
CAS Code # 24P10
Trade in Services, Percentage of GDP
Source: Latest country data obtained from national data
sources or IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm. Benchmarking
data from the World Development Indicators, most recent
publication, series BG.GSR.NFSV.GD.ZS.
Definition: Trade in services is the sum of service exports
and imports divided by the value of GDP, all in current U.S.
dollars.
Coverage: Data available for about 80 USAID countries.
CAS Code # 24P11
Concentration of Exports
Source: Constructed with ITC COMTRADE data by
aggregating the value for the top three export product groups
(SITC Rev.3) and dividing by total exports. Raw data:
http://www.intracen.org/tradstat/sitc3-3d/indexre.htm
Definition: The percentage of a country’s total merchandise
exports consisting of the top three products, disaggregated at
the SITC (Rev. 3) 3-digit level.
Coverage: Available for about 74 USAID countries.
Data Quality: Smuggling is a serious problem in some
countries. For countries that do not report trade data to the
United Nations, ITC uses partner country data. There are a
number of shortcomings with this approach: ITC does not
cover trade with other nonreporting countries; transshipments
may hide the actual source of supply; and reporting standards
include transport cost and insurance in measuring exports but
exclude these items when measuring imports.
CAS Code # 24S1
Inward FDI Potential Index
Source: UNCTAD. Indicator is available at
http://www.unctad.org/Templates/WebFlyer.asp?intItemID=
2472&lang=1.
Definition: Inward FDI Potential Index measures an
economy’s attractiveness to foreign investors, capturing
factors (apart from market size) that are expected to have an
impact. The index ranges in value from 0 (for very poor
performance) to 1 (for excellent performance). It is an
unweighted average of the scores of 12 normalized economic
and social variables.
Coverage: Data are available for about 77 USAID countries.
CAS Code # 24S2
Net Barter Terms of Trade
Source: World Development Indicators, most recent
publication, series TT.PRI.MRCH.XD.WD
Definition: Net barter terms of trade are calculated as the
ratio of the export price index to the corresponding import
price index measured relative to the base year 2000.
Coverage: Data are available for about 51 USAID countries.
CAS Code # 24S3
Real Effective Exchange Rate (REER)
Source: IMF Article IV consultation reports:
www.imf.org/external/np/sec/aiv/index.htm;
Definition: The REER is an index number with base
2000=100, which measures the value of a currency against a
weighted average of foreign currencies. It is calculated as the
nominal effective exchange rate divided by a price deflator or
index of costs. The IMF defines the REER so that an increase
in the value represents a real appreciation of the home
currency, and a decrease represents a real depreciation.
Coverage: Information on coverage is not easily accessible.
Data Quality: Changes in real effective exchange rates
should be interpreted with caution. For many countries the
weights from 1990 onward take into account trade in 1988-
90, and an index of relative changes in consumer prices is
used as the deflator.
CAS Code # 24S4
Structure of Merchandise Exports
Source: World Development Indicators, most recent
publication. Exports from five categories are used: Food
exports series TX.VAL.FOOD.ZS.UN; Agricultural raw
materials exports series TX.VAL.AGRI.ZS.UN;
Manufactures exports series TX.VAL.MANF.ZS.UN; Ores
and metals exports series TX.VAL.MMTL.ZS.UN; and Fuel
exports series TX.VAL.FUEL.ZS.UN.
Definition: This indicator reflects the composition of
merchandise exports by major commodity groups—food,
agricultural raw materials, fuels, ores and metals, and
manufactures.
Coverage: Data are available for about 78 USAID countries.

T ECHNICAL N OTES B - 31
Data Quality: The classification of commodity groups
follows the Standard International Trade Classification
(SITC) revision 1, but most countries report using later
revisions of the SITC. Tables are used to convert data
reported in one system to another and this may introduce
errors of classification. Shares may not sum to 100 percent
because of unclassified trade.
CAS Code # 24S5
Trade Policy Index
Source: Index of Economic Freedom, Heritage Foundation:
http://www.heritage.org/Index/. The Trade Policy Score
(index) is one component of the Index of Economic Freedom.
Definition: The index measures the degree to which
government hinders the free flow of foreign commerce, based
on a country’s weighted average tariff rate (weighted by
imports from the country’s trading partners), with
adjustments for non-tariff barriers and corruption in the
customs service. The countries are ranked on a 0-to-100
scale, with a higher score representing greater freedom (low
barriers to trade)—a switch from the 5-1 ranking of previous
Indexes (in which lower numbers denoted greater freedom).
Coverage: Data are available for about 83 USAID countries.
Data Quality: The index is subjective and at times
inconsistent in its treatment of tariffs.
CAS Code # 24S6
Ease of Trading Across Borders Ranking
Source: World Bank, Doing Business, Trading Across
Borders category:
http://www.doingbusiness.org/ExploreTopics/TradingAcross
Borders/
Definitions: The 181 economies covered by the Doing
Business report are ranked on the ease with which one may
import into and export out of the economy. The ranking is
based on a simple average of the economy’s ranking on each
of the composite indicators for Trading Across Borders:
number of documents to import and export, cost to import
and export, and time to import and export.
Coverage: Data are available for nearly all USAID countries.
CAS Code # 24S7
ECONOMIC INFRASTRUCTURE
Internet Users per 100 people
Source: World Development Indicators, most recent
publication series IT.NET.USER.P2, derived from the
International Telecommunication Union database.
Definition: Indicator quantifies the number of Internet users,
defined as those with access to the worldwide network, per
100 people.
Coverage: Data are available for about 88 USAID countries.
CAS Code # 25P1
Logistics Performance Index, Infrastructure
Source: World Bank, Logistics Performance Index (LPI)
www.worldbank.com/lpi. The Infrastructure Quality is one
component of the Logistics Performance Index.
Definition: The LPI ranks countries on a scale of 1 to 5
(lowest to highest) in terms of IT, telecommunications and
transportation infrastructure. It is based on a survey of more
than 800 logistics professionals who each operate in at least
eight countries.
Coverage: Data are available for about 80 USAID countries.
CAS Code # 25P2
Telephone Density, Fixed Line and Mobile per 100 people
Source: World Development Indicators, most recent
publication series IT.TEL.TOTL.P3, derived from the
International Telecommunication Union database.
Definition: The indicator is the sum of subscribers to
telephone mainlines and mobile phones per 100 people.
Fixed lines represent telephone mainlines connected to the
public switched telephone network. Mobile phone
subscribers refer to users of cellular-based technology with
access to the public switched telephone network.
Coverage: Data are available for about 88 USAID countries.
CAS Code #25P3
Overall Infrastructure Quality Index
Source: Global Competitiveness Report, World Economic
Forum
http://www.weforum.org/en/initiatives/gcp/Global%20Comp
etitiveness%20Report/index.htm.
Definition: The index measures executives’ perceptions of
general infrastructure in their respective country. Executives
grade, on a scale from 1 to 7, whether general infrastructure
in their country is poorly developed (1) or among the best in
the world (7).
Coverage: Data are available for about 52 USAID countries.
Data Quality: Comparisons between countries are difficult
because the data are based on executives’ perceptions.
CAS Code # 25P4
Quality of infrastructure—Railroads, Ports, Air
Transport and Electricity
Source: Global Competitiveness Report, World Economic
Forum
http://www.weforum.org/documents/gcr0809/index.html.
Definitions: The index measures executives’ perceptions of
general infrastructure in their respective country. Executives
grade, on a scale from 1 to 7, whether railroads, ports, air
transport, and electricity are poorly developed (1) or among
the best in the world (7).
Coverage: Data are available for about 52 USAID countries.
Data Quality: Comparisons between countries are difficult
because the data are based on executive perceptions.
CAS Code #25S1
Roads, paved (% total)
Source: World Development Indicators, most recent
publication series IS.ROD.PAVE.ZS
Definitions: Paved roads are roads surfaced with crushed
stone (macadam) and hydrocarbon binder or bituminized
agents, with concrete, or with cobblestones.
Coverage: Data are available for nearly all USAID countries.
CAS Code #25S2
SCIENCE AND TECHNOLOGY
FDI Technology Transfer Index
Source: Global Competitiveness Report, World Economic
Forum
http://www.weforum.org/documents/gcr0809/index.html.
Definition: The index measures executives’ perceptions of
FDI as a source of new technology for the country.

B - 32 T ECHNICAL N OTES
Executives grade, on a scale from 1 to 7, whether foreign
direct investment in their country brings little new
technology (1), or is an important source of new technology
(7).
Coverage: Data are available for about 52 USAID countries.
Data Quality: Comparisons between countries are difficult
because the data are based on executive perceptions.
CAS Code # 26P1
Availability of Scientists and Engineers Index
Source: Global Competitiveness Report, World Economic
Forum
http://www.weforum.org/documents/gcr0809/index.html.
Definitions: The index measures executives’ perceptions of
the availability of scientists and engineers in their respective
country. Executives grade, on a scale from 1 to 7, whether
scientists and engineers in their country are nonexistent (1) or
rare, or widely available (7).
Coverage: Data are available for about 52 USAID countries.
Data Quality: Comparisons between countries are difficult
because the data are based on executive perceptions.
CAS Code #26P2
Science and Technology Journal Articles, per Million
People
Source: World Development Indicators, most recent
publication, series IP.JRN.ARTC.SC
Definitions: The indicator refers to published scientific and
engineering articles in physics, biology, chemistry,
mathematics, clinical medicine, biomedical research,
engineering and technology, and earth and space sciences per
one million population.
Coverage: Data are available for about 82 USAID countries.
CAS Code #26P3
IPR Protection Index
Source: Global Competitiveness Report, World Economic
Forum
http://www.weforum.org/documents/gcr0809/index.html.
Definitions: The index measures executives’ perceptions of
the availability of the quality of intellectual property rights
protection in their respective country. The scale ranges from
1(for poorly enforced) to 7 (among the best in the world).
Coverage: Data are available for about 52 USAID countries.
Data Quality: Comparisons between countries are difficult
because the data are based on executive perceptions.
CAS Code #26P4
HEALTH
HIV Prevalence
Source: UNAIDS for most recent country data:
http://data.unaids.org/pub/GlobalReport/2008/20080813_gr0
8_prev1549_1990_2007_en.xls . World Development
Indicators, most recent publication for benchmark data, series
SH.DYN.AIDS.ZS.
Definition: Percentage of people ages 15–49 who are infected
with HIV.
Coverage: Data are available for about 79 USAID countries.
Data Quality: UNAIDS/WHO estimates are based on all
available data, including surveys of pregnant women,
population-based surveys, household surveys conducted by
Kenya, Mali, Zambia, and Zimbabwe, and other surveillance
information.
CAS Code # 31P1
Life Expectancy at Birth
Source: World Development Indicators, most recent
publication, (SP.DYN.LE00.IN)
Definition: Life expectancy at birth indicates the number of
years a newborn infant would live on average if prevailing
patterns of mortality at the time of his or her birth were to
stay the same throughout his or her life.
Coverage: Data are available for about 88 USAID countries.
Data Quality: Life expectancy at birth is estimated on the
basis of vital registration or the most recent census/survey.
Extrapolations may not be reliable for monitoring changes in
health status or for comparative analytical work.
CAS Code # 31P2
Maternal Mortality Rate
Source: UN Millennium Indicators Database,
http://millenniumindicators.un.org/unsd/mdg/Data.aspx
based on WHO, UNICEF and UNFPA data.
Definition: The indicator is the number of women who die
during pregnancy and childbirth, per 100,000 live births.
Coverage: Data are available for about 87 USAID countries.
Data Quality: Household surveys attempt to measure
maternal mortality by asking respondents about survival of
sisters. The estimates pertain to 12 years or so before the
survey, making them unsuitable for monitoring recent
changes.
CAS Code # 31P3
Access to Improved Sanitation
Source: World Development Indicators, most recent
publication, series SH.STA.ACSN.
Definition: The indicator is the percentage of population with
at least adequate excreta disposal facilities (private or shared,
but not public) that can effectively prevent human, animal,
and insect contact with excreta.
Coverage: Data are available for about 82 USAID countries.
CAS Code #31S1
Access to Improved Water Source
Source: World Development Indicators, most recent
publication series SH.H2O.SAFE.ZS
Definition: The indicator is the percentage of the population
with reasonable access to an adequate amount of water from
an improved source, such as a household connection, public
standpipe, borehole, protected well or spring, or rain water
collection.
Coverage: Data are available for about 83 USAID countries.
Data Quality: Access to drinking water from an improved
source does not ensure that the water is adequate or safe.
CAS Code # 31S2
Births Attended by Skilled Health Personnel
Source: World Development Indicators, most recent
publication, series SH.STA.BRTC.ZS.
Definition: The indicator is the percentage of deliveries
attended by personnel trained to give the necessary
supervision, care, and advice to women during pregnancy,

T ECHNICAL N OTES B - 33
labor, and the postpartum period, to conduct interviews on
their own, and to care for newborns.
Coverage: Data are available for about 62 USAID countries.
Data Quality: Data may not reflect improvements in
maternal health; maternal deaths are underreported; and rates
of maternal mortality are difficult to measure.
CAS Code # 31S3
Child Immunization Rate
Source: World Development Indicators, most recent
publication, estimated by averaging two series:
Immunization, DPT (% of children ages 12–23 months)
(SH.IMM.IDPT) and Immunization, measles (% of children
ages 12–23 months) (SH.IMM.MEAS).
Definition: Percentage of children under one year of age
receiving vaccination coverage for four diseases: measles and
diphtheria, pertussis (whopping cough), and tetanus (DDPT).
Coverage: Data are available for about 88 USAID countries.
CAS Code #31S4
Prevalence of Child Malnutrition—Weight for Age
Source: World Development Indicators, most recent
publication, series SH.STA.MALN.ZS.
Definition: The indicator is based on the percentage of
children under age five whose weight for age is more than
minus two standard deviations below the median for the
international reference population ages 0–59 months.
Coverage: Data are available for about 55 USAID countries.
CAS Code # 31S5
Public Health Expenditure, Percentage of GDP
Source: Latest data for host country is obtained from the
MCC:
http://www.mcc.gov/selection/scorecards/2007/index.php.
International benchmarking data from World Development
Indicators, most recent publication (SH.XPD.PUBL.ZS),
based on World Health Organization, World Health Report,
and updates and from the OECD, supplemented by World
Bank poverty assessments and country and sector studies.
Definition: Public health expenditure consists of recurrent
and capital spending from government (central and local)
budgets, external borrowings and grants (including donations
from international agencies and nongovernmental
organizations), and social (or compulsory) health insurance
funds.
Coverage: Data are available for about 88 USAID countries.
CAS Code #31S6
EDUCATION
Net Primary Enrollment Rate—Female, Male and Total
Source: UNESCO Institute for Statistics,
http://stats.uis.unesco.org/ReportFolders/reportfolders.aspx
Definition: The indicator measures the proportion of the
population of the official age for primary, secondary, or
tertiary education according to national regulations who are
enrolled in primary schools. Primary education provides
children with basic reading, writing, and mathematics skills
along with an elementary understanding of such subjects as
history, geography, natural science, social science, art, and
music.
Coverage: Data are available for about 80 USAID countries.
Data Quality: Enrollment rates are based on data collected
during annual school surveys, which are typically conducted
at the beginning of the school year, and do not reflect actual
rates of attendance during the school year. In addition, school
administrators may report exaggerated enrollments because
teachers often are paid proportionally to the number of pupils
enrolled. The indicator does not measure the quality of the
education provided.
CAS Code # 32P1
Primary Completion Rate—Total
Source: World Development Indicators, most recent
publication, series SE.PRM.CMPT.ZS (total). Based on data
from United Nations Education, Scientific, and Cultural
Organization (UNESCO) Institute of Statistics.
Definition: Primary completion rate is the percentage of
students completing the last year of primary school. It is
calculated by taking the total number of students in the last
grade of primary school, minus the number of repeaters in
that grade, divided by the total number of children of official
graduation age.
Coverage: Data are available for about 128 USAID countries
CAS Code # 32P2
Youth Literacy Rate—Female, Male, and Total
Source: World Development Indicators, most recent
publication, series SE.ADT.1524.LT.ZS.
Definition: The indicator is an estimate of the percent of
people ages 15–24 who can, with understanding, read and
write a short, simple statement on their everyday life.
Coverage: Data are available for about 67 USAID countries.
Data Quality: Statistics are out of date by two to three years.
CAS Code #32P3
Net Secondary Enrollment Rate, Total
Source: World Development Indicators, most recent
publication, series SE.SEC.NENR. Based on data from the
United Nations Educational, Scientific, and Cultural
Organization (UNESCO) Institute for Statistics.
Definitions: Net enrollment ratio is the ratio of children of
official school age based on the International Standard
Classification of Education 1997 who are enrolled in school
to the population of the corresponding official school age.
Secondary education completes the provision of basic
education that began at the primary level and aims at laying
the foundations for lifelong learning and human development
by offering more subject- or skill-oriented instruction using
more specialized teachers.
Coverage: Not available for draft.
Data Quality: Break in series between 1997 and 1998 due to
change from International Standard Classification of
Education (ISCED) 76 to ISCED97. Recent data are
provisional.
CAS Code #32P4
Gross Tertiary Enrollment Rate, Total
Source: World Development Indicators, most recent
publication, series SE.TER.ENRR. Based on data from the
UNESCO Institute for Statistics.
Definitions: Gross enrollment ratio is the ratio of total
enrollment, regardless of age, to the population of the age
group that officially corresponds to the level of education
shown. Tertiary education, whether or not to an advanced
research qualification, normally requires, as a minimum

B - 34 T ECHNICAL N OTES
condition of admission, the successful completion of
education at the secondary level.
Coverage: Not available for draft.
Data Quality: Break in series between 1997 and 1998 due to
change from International Standard Classification of
Education (ISCED) 76 to ISCED97. Recent data are
provisional.
CAS Code #32P5
Expenditure on Primary Education, Percentage of GDP
Source: Millennium Challenge Corporation:
http://www.mcc.gov/selection/scorecards/2007/index.php.
Definition: The indicator is the total expenditures on
education by all levels of government, as a percent of GDP.
Coverage: Data are available for about 58 USAID countries.
Data Quality: The MCC obtains the data from national
sources through U.S. embassies.
CAS Code #32S1
Educational Expenditure per Student, Percentage of GDP
per capita—Primary, Secondary and Tertiary
Source: World Development Indicators, most recent
publication series SE.XPD.PRIM.PC.ZS (primary);
SE.XPD.SECO.PC.ZS (secondary); and
SE.XPD.TERT.PC.ZS (tertiary).
Definition: Public expenditure per student (primary,
secondary or tertiary) is defined as the public current
expenditure on education divided by the total number of
students, by level, as a percentage of GDP per capita.
Coverage: Data are available for about 50, 47, and 45
USAID countries (for primary, secondary, and tertiary
expenditure, respectively).
Data Quality: Education statistics should be interpreted with
caution because the data are out of date by 2 or 3 years; also,
the statistics reflects solely public spending, generally
excluding spending by religious schools, which play a
significant role in many developing countries. Data for some
countries and for some years refer to spending by the
ministry of education only.
CAS Code # 32S2
Pupil-teacher Ratio, Primary School
Source: World Development Indicators, most recent
publication series SE.PRM.ENRL.TC.ZS.
Definition: Primary school pupil-teacher ratio is the number
of pupils enrolled in primary school divided by the number of
primary school teachers (regardless of their teaching
assignment).
Coverage: Data are available for about 76 USAID countries.
Data Quality: The indicator does not take into account
differences in teachers’ academic qualifications, pedagogical
training, professional experience and status, teaching
methods, teaching materials and variations in classroom
conditions – all factors that could also affect the quality of
teaching/learning and pupil performance.
CAS Code # 32S3
EMPLOYMENT AND WORKFORCE
Labor Force Participation Rate
Source: World Development Indicators, most recent
publication series: SL.TLF.CACT.ZS. Based on data from
International Labour Organization (ILO).
Definition: The proportion of the population ages 15 and
older that is economically active: all people who supply labor
for the production of goods and services during a specified
period. It includes both the employed and the unemployed.
Coverage: Data are available for about 88 USAID countries.
CAS Code #33P1
Rigidity of Employment Index
Source: World Bank, Doing Business, Employing workers
category:
http://www.doingbusiness.org/ExploreTopics/EmployingWor
kers/
Definition: Rigidity of employment index is a measure of
labor market rigidity constructed as the average of the
Difficulty of Hiring index, Rigidity of Hours index and
Difficulty of Firing index. Index ranges in value from 0
(minimum rigidity) to 100 (maximum rigidity).
Coverage: Data are available for nearly all USAID countries.
Data Quality: Subindices are compiled by the World Bank
from survey responses to in-country specialists.
CAS Code # 33P2
Size and Growth of the Labor Force
Source: Size of labor force from World Development
Indicators (SL.TLF.TOTL.IN); annual percentage change
calculated from size data.
Definition: The indicator measures the size of the labor
supply, and its annual percent change. Labor force is made
up of people who meet the International Labor Organization
definition of the economically active population: all people
who are able to supply labor for the production of goods and
services during a specified period, including both the
employed and the unemployed. Although national practices
vary in the treatment of groups such as the armed forces and
seasonal or part-time workers, in general, the labor force
includes the armed forces, the unemployed, and first-time
job-seekers, but excludes homemakers and other unpaid
caregivers and workers in the informal sector.
Coverage: Data are available for about 88 USAID countries.
CAS Code #33P3
Unemployment Rate
Source: World Development Indicators, most recent
publication series SL.UEM.TOTL.ZS.
Definition: The unemployment rate refers to the share of the
labor force that is without work but available for and seeking
employment. For this purpose, informal sector workers and
own-account workers (including subsistence farmers) are
counted as employed.
Coverage: Data are available for about 50 USAID countries.
Data Quality: Definitions of labor force and unemployment
differ by country, making international comparisons
inaccurate.
CAS Code # 33P4
Economically Active Children, Percentage Children Ages
7-14
Source: World Development Indicators, most recent
publication series SL.TLF.0714.ZS. Derived from the
Understanding Children's Work project based on data from
ILO, UNICEF, and the World Bank.
Definitions: Economically active children refer to children
involved in economic activity for at least one hour in the
reference week of the survey.

T ECHNICAL N OTES B - 35
CAS Code # 33P5
Firing Costs, Weeks of Wages
Source: World Bank, Doing Business, Employing Workers
Category:
http://www.doingbusiness.org/ExploreTopics/EmployingWor
kers/ .
Definitions: The firing cost indicator measures the cost of
advance notice requirements, severance payments, and
penalties due when terminating a redundant worker,
expressed in weekly wages. One month is recorded as 4 and
1/3 weeks.
Coverage: Data available for nearly all USAID countries.
CAS Code # 33S1
AGRICULTURE
Agriculture Value Added per Worker
Source: World Development Indicators, most recent
publication series EA.PRD.AGRI.KD, derived from World
Bank national accounts files and Food and Agriculture
Organization, Production Yearbook and data files.
Definition: Agriculture value added per worker is a basic
measure of labor productivity in agriculture. Value added in
agriculture measures the output of the agricultural sector
(ISIC divisions 1–5)—forestry, hunting, fishing, cultivation
of crops, and livestock production—less the value of
intermediate inputs. Data are in constant 2000 U.S. dollars.
Coverage: Data are available for about 80 USAID countries.
CAS Code # 34P1
Cereal Yield
Source: World Development Indicators, most recent
publication series AG.YLD.CREL.KG based on Food and
Agriculture Organization Production Yearbook and data files.
Definition: Cereal yield, measured as kilograms per hectare
of harvested land, includes wheat, rice, maize, barley, oats,
rye, millet, sorghum, buckwheat, and mixed grains.
Production data on cereals relate to crops harvested for dry
grain only.
Coverage: Data are available for about 84 USAID countries.
Data Quality: Data on cereal yield may be affected by a
variety of reporting and timing differences. The FAO
allocates production data to the calendar year in which the
bulk of the harvest took place. But most of a crop harvested
near the end of a year will be used in the following year.
Cereal crops harvested for hay or harvested green for food,
feed, or silage, and those used for grazing, are generally
excluded. But millet and sorghum, which are grown as feed
for livestock and poultry in Europe and North America, are
used as food in Africa, Asia, and countries of the former
Soviet Union. So some cereal crops are excluded from the
data for some countries and included elsewhere, depending
on their use.
CAS Code # 34P2
Growth in Agricultural Value-Added
Source: The latest country data are taken from national data
sources or from IMF Article IV consultation reports:
http://www.imf.org/external/np/sec/aiv/index.htm. The
benchmarking data are from World Development Indicators,
most recent publication series NV.AGR.TOTL.KD.ZG
Definition: The indicator measures the annual growth rate for
agricultural value added, in constant local currency. Regional
group aggregates are based on constant 2000 U.S. dollars.
Agriculture corresponds to ISIC divisions 1–5 and includes
forestry, hunting, and fishing, as well as cultivation of crops
and livestock production. Value added is the net output of a
sector after all outputs are added up and intermediate inputs
are subtracted. It is calculated without deductions for
depreciation of fabricated assets or depletion and degradation
of natural resources.
Coverage: Data are available for about 84 USAID countries.
CAS Code # 34P3
Fertilizer Consumption (100 grams per hectare of arable
land)
Source: World Development Indicators, most recent
publication series AG.CON.FERT.ZS, derived from Food
and Agriculture Organization Production Yearbook and data
files.
Definition: Fertilizer consumption (100 grams per hectare of
arable land) measures the quantity of plant nutrients used per
unit of arable land. Fertilizer products cover nitrogenous,
potash, and phosphate fertilizers (including ground rock
phosphate). Traditional nutrients--animal and plant manuresare
not included. The time reference for fertilizer
consumption is the crop year (July through June). Arable
land includes land defined by the FAO as land under
temporary crops (double-cropped areas are counted once),
temporary meadows for mowing or for pasture, land under
market or kitchen gardens, and land temporarily fallow. Land
abandoned as a result of shifting cultivation is excluded.
Coverage: Data available for
CAS Code #34P4
Agricultural Policy Costs Index
Source: Global Competitiveness Report, World Economic
Forum
http://www.weforum.org/documents/gcr0809/index.html.
Definition: The index measures executives’ perceptions of
agricultural policy costs in their respective country.
Executives grade, on a scale from 1 to 7, whether the cost of
agricultural policy in a given country is excessively
burdensome (1), or balances all economic agents’ interests
(7).
Coverage: Data are available for about 52 USAID countries.
Data Quality: Comparisons between countries are difficult
because the data are based on executives’ perceptions.
CAS Code # 34S1
Crop Production Index
Source: World Development Indicators, most recent
publication series AG.PRD.CROP.XD, based on FAO
statistics.
Definition: Crop production index shows agricultural
production for each year relative to the period 1999–2001 =
100. The index includes production of all crops except fodder
crops. Regional and income group aggregates for the FAO’s
production indices are calculated from the underlying values
in international dollars, normalized to the base period.
Coverage: Data are available for about 85 USAID countries.
Data Quality: Regional and income group aggregates for the
FAO’s production indices are calculated from the underlying
values in international dollars, normalized to the base period
1999–2001. The FAO obtains data from official and
semiofficial reports of crop yields, area under production,
and livestock numbers. If data are not available, the FAO
makes estimates. To ease cross-country comparisons, the
FAO uses international commodity prices to value production

B - 36 T ECHNICAL N OTES
expressed in international dollars (equivalent in purchasing
power to the U.S. dollar). This method assigns a single price
to each commodity so that, for example, one metric ton of
wheat has the same price regardless of where it was
produced. The use of international prices eliminates
fluctuations in the value of output due to transitory
movements of nominal exchange rates unrelated to the
purchasing power of the domestic currency.
Coverage: Data are available for about 85 USAID countries.
CAS Code # 34S2
Livestock Production Index
Source: World Development Indicators, most recent
publication series AG.PRD.LVSK.XD, based on FAO.
Definition: Livestock production index shows livestock
production for each year relative to the base period 1999–
2001=100. The index includes meat and milk from all
sources, dairy products such as cheese, and eggs, honey, raw
silk, wool, and hides and skins.
Coverage: Data are available for about 85 USAID countries.
Data Quality: See comments on the Crop Production Index.
CAS Code # 34S3
Agriculture Export Growth
Source: World Development Indicators, most recent
publication series TX.VAL.AGRI.ZS.UNs, Agricultural raw
materials exports (% of merchandise exports), based on
World Bank staff estimates from the COMTRADE database
maintained by the United Nations Statistics Division; and
series TX.VAL.MRCH.CD.WT, Merchandise exports
(current US$), based on data from the World Trade
Organization.
Definitions: Agricultural raw materials comprise SITC
section 2 (crude materials except fuels), excluding divisions
22, 27 (crude fertilizers and minerals excluding coal,
petroleum, and precious stones), and 28 (metalliferous ores
and scrap). Merchandise exports show the f.o.b. value of
goods provided to the rest of the world valued in U.S. dollars.
Data are in current U.S. dollars. The indicator is calculated
by multiplying agricultural raw materials by merchandise
exports. The annual growth rate is then calculated from the
resulting series.
Coverage: Not available for draft.
CAS Code # 34S4